HOI-Learning-List

Some recent (2015-now) Human-Object Interaction Learning studies. If you find any errors or problems, please don't hesitate to let me know.

A list of Transfomer-based vision works https://github.com/DirtyHarryLYL/Transformer-in-Vision.

Image Dataset/Benchmark

CAL (arXiv 2024.1), a contact-driven affordance learning dataset [Paper], [Project]
SynHOI (arXiv 2023.5), synthetic HOI data [Paper]
HICO-DET-SG, V-COCO-SG (new splits of HICO-DET and V-COCO) [Paper], [Code]
Bongard-HOI [Paper], [Code]
SWiG-HOI, [Paper], [Website]
New Metric: mPD, [Paper], [Code]
DIABOLO [Paper], [Website]
HOI-COCO (CVPR2021) [Website]
PaStaNet-HOI (TPAMI2021) [Benchmark]
HAKE (CVPR2020) [YouTube] [bilibili] [Website] [Paper] [HAKE-Action-Torch] [HAKE-Action-TF]
Ambiguous-HOI (CVPR2020) [Website] [Paper]
HICO-DET (WACV2018) [Website] [Paper]
HCVRD (AAAI2018) [Website] [Paper]
V-COCO (May 2015) [Website] [Paper]
HICO (ICCV2015) [Website] [Paper]
OpenImage [Website] [Paper]
PIC [Website]

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Video HOI Datasets

MOMA [Paper], [Project]
MPHOI-72 RGB-D, [Paper], [Project]
VidHOI [Paper], [Project]
AVA [Website], HOIs (human-object, human-human), and pose (body motion) actions
Action Genome [Website], action verbs and spatial relationships
CAD120 [Paper], [Website]
Sth-else [Paper], [Website]

3D HOI Datasets

ParaHome, [Paper], [Project]
BallPlay, [Paper], [Project]
COINS, [Paper], [Project]
COUCH, [Paper], [Project]
HULC, [Paper], [Project]
CHAIRS, [Paper], [Project]
GRAB, [Paper], [Project]
HUMANISE, [Paper], [Project]
BEHAVE, [Paper], [Project]
GraviCap, [Paper], [Project]

Survey

Human object interaction detection: Design and survey (Image and Vision Computing 2022), [Paper]

Method

HOI Image Generation

ReCorD: Reasoning and Correcting Diffusion for HOI Generation (ACM MM 2024) [Paper], [Project]
InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model (CVPR 2024) [Paper], [Project]
Person in Place: Generating Associative Skeleton-Guidance Maps for Human-Object Interaction Image Editing (CVPR 2024) [Paper], [Code]
VirtualModel: Generating Object-ID-retentive Human-object Interaction Image by Diffusion Model for E-commerce Marketing (arXiv 2024.5) [Paper] [Code]
Exploiting Relationship for Complex-scene Image Generation (arXiv 2021.04) [Paper]
Specifying Object Attributes and Relations in Interactive Scene Generation (arXiv 2019.11) [Paper]

HOI Recognition: Image-based, to recognize all the HOIs in one image.

RAM++ (arXiv'23) [Paper], [Code]
OpenTAP (ECCV'22) [Paper], [Code]
RelViT (ICLR'22) [Paper], [Code]
DEFR (arXiv 2021.12) [Paper]
Interaction Compass (ICCV 2021) [Paper]
DEFR-CLIP (arXiv 2021.07) [Paper]
PaStaNet: Toward Human Activity Knowledge Engine (CVPR2020) [Code] [Data] [Paper] [YouTube] [bilibili]
Pairwise (ECCV2018) [Paper]
Attentional Pooling for Action Recognition (NIPS2017) [Code] [Paper]
Learning Models for Actions and Person-Object Interactions with Transfer to Question Answering (ECCV2016) [Code] [Paper]
Contextual Action Recognition with R*CNN (ICCV2015) [Code] [Paper]
HOCNN (ICCV2015) [Code] [Paper]
SGAP-Net (AAAI2020) [Paper]

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Unseen or zero-shot learning (image-level recognition).

HTS (ICIP 2023) [Paper]
ICompass (ICCV2021) [Paper], [Code]
Compositional Learning for Human Object Interaction (ECCV2018) [Paper]
Zero-Shot Human-Object Interaction Recognition via Affordance Graphs (Sep. 2020) [Paper]

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HOI for Robotics.

HOI4ABOT: Human-Object Interaction Anticipation for Assistive roBOTs (CORL 2023) [Paper], [Project]
Human–object interaction prediction in videos through gaze following (CVIU 2023) [Paper], [Project]

HOI Detection: Instance-based, to detect the human-object pairs and classify the interactions.

HOIGen (ACM MM 2024), [Paper], [Code]
DiffusionHOI (NeurIPS 2024), [Paper], [Code]
CEFA (ACM MM 2024), [Paper], [Code]
CO-HOI (arXiv 2024), [Paper]
HOIGen (ACM MM 2024), [Paper], [Code]
CMMP (ECCV 2024), [Paper], [Code]
CycleHOI (arXiv 2024), [Paper]
GeoHOI (arXiv 2024), [Paper], [Code]
SICHOI (CVPR 2024), [Paper]
Pose-Aware (CVPR 2024), [Paper]
BCOM (CVPR 2024), [Paper]
MP-HOI (CVPR 2024), [Paper], [Project]
DP-HOI (CVPR 2024), [Paper], [Code]
DPADN (AAAI 2024), [Paper], [Code]
KI2HOI (arXiv 2024), [Paper]
SCTC (AAAI 2024), [Paper]
OBPA-Net (PRCV 2023), [Paper], [Code]
MLKD (WACV2024), [Paper], [Code]
SBM (PRCV2023), [Paper]
UnionDet (arXiv 2023), [Paper]
SCA (arXiv 2023), [Paper]
HCVC (arXiv 2023), [Paper]
GFIN (NN 2023), [Paper]
LOGICHOI (NeurIPS 2023), [Paper], [Code]
CLIP4HOI (NeurIPS 2023), [Paper]
UniHOI (NeurIPS 2023), [Paper], [Code]
SG2HOI (arXiv 2023), [Paper]
SQAB (Displays 2023), [Paper]
Mult-Step (ACMMM 2023), [Paper]
PDN (PR 2023), [Paper]
ICDT (ICANN 2023), [Paper], [Code]
ScratchHOI (ICIP 2023), [Paper]
ADA-CM (ICCV 2023), [Paper], [Code]
HODN (TMM 2023), [Paper]
RLIPv2 (ICCV 2023), [Paper], [Code]
AGER (ICCV 2023), [Paper], [Code]
Diagnosing Human-object Interaction Detectors (arXIv 2023), [Paper], [Code]
Compo (ICME 2023), [Paper]
PViC (ICCV 2023), [Paper], [Code]
VIL (ACM MM 2023), [Paper]
RmLR (ICCV 2023), [Paper]
PSN (arXiv 2023), [Paper]
SOV-STG (arXiv 2023), [Paper], [Code]
Shikra (arXiv 2023), [Paper], [Code]
HOKEM (arXiv 2023), [Paper]
SQA (ICASSP 2023), [Paper], [Code]
OpenCat (CVPR 2023), [Paper]
DiffHOI (arXiv 2023.5), [Paper]
ViPLO (CVPR 2023), [Paper], [Code]
MUREN (CVPR 2023), [Paper], [Project]
HOICLIP (CVPR 2023), [Paper], [Code]
CQL (CVPR 2023), [Paper], [Code]
UniVRD (arXiv 2023), [Paper]
SKGHOI (arXiv 2023), [Paper]
Weakly-HOI-CLIP (ICLR 2023), [Paper], [Code]
FGAHOI (arXiv 2023), [Paper], [Code]
PR-Net (arXiv 2023), [Paper]
PQNet (MMAsia 2022), [Paper]
MHOI (TCSVT 2022), [Paper]
RLIP (NeurIPS 2022), [Paper], [Code]
PartMap (ECCV2022), [Paper], [Code]
K-BAN (arXiv 2022), [Paper]
SGCN4HOI (IEEE SMC 2022), [Paper]
HQM (ECCV 2022), [Paper], [Code]
ODM (ECCV 2022), [Paper]
SDT (arXiv 2022), [Paper]
DOQ (CVPR 2022), [Paper], [Code]
STIP (CVPR 2022), [Paper]
DT (CVPR 2022), [Paper]
IF (CVPR 2022), [Paper], [Code]
CPC (CVPR 2022), [Paper], [Code]
CATN (CVPR 2022), [Paper]
SSRT (CVPR 2022), [Paper]
GEN-VLKT (CVPR 2022), [Paper], [Code]
MSTR (CVPR 2022), [Paper]
Iwin (ECCV 2022), [Paper]
RGBM (arXiv 2022.2), [Paper]
GPV-2 (ECCV 2022), [Paper], [Project]
OC-Immunity (AAAI 2022) [Paper], [Code]
OCN (AAAI 2022) [Paper], [Code]
QAHOI (arXiv 2021) [Paper], [Code]
PhraseHOI (AAAI 2022) [Paper]
DEFR (arXiv 2021.12) [Paper]
UPT (CVPR 2022) [Paper], [Code]
HRNet (TIP 2021) [Paper]
ACP++ (TIP 2021) [Paper], [Code]
SG2HOI (ICCV 2021) [Paper]
CDN (NeurIPS 2021) [Paper], [Code]
GTNet (arXiv 2021.8) [Paper], [Code]
HOI-MO-Net (IVC 2021) [Paper]
IPGN (TIP 2021.7) [Paper]
SCG (ICCV 2021, SAG, v2) [Paper], [Code]
Human Object Interaction Detection using Two-Direction Spatial Enhancement and Exclusive Object Prior (arXiv) [Paper]
PST (ICCV2021) [Paper]
RR-Net (arXiv 2021.5) [Paper]
HOTR (CVPR2021) [Paper], [Code]
GGNet (CVPR2021) [Paper], [Code]
ATL (CVPR2021) [Paper], [Code]
FCL (CVPR2021) [Paper], [Code]
AS-Net (CVPR2021) [Paper], [Code]
End-to-End Human Object Interaction Detection with HOI Transformer (CVPR2021), [Paper], [Code]
QPIC (CVPR2021) [Paper], [Code]
TIN (TPAMI2021) [Paper], [Code]
IDN (NeurIPS2020) [Paper] [Code]
DIRV (AAAI2021) [Paper]
DecAug (AAAI2021) [Paper]
OSGNet (IEEE Access) [Paper]
PFNet (CVM) [Paper]
UniDet (ECCV2020) [Paper]
DRG (ECCV2020) [Paper] [Code]
FCMNet (ECCV2020) [Paper]
Contextual Heterogeneous Graph Network for Human-Object Interaction Detection (ECCV2020) [Paper]
PD-Net (ECCV2020) [Paper-1] [Paper-2] [Code]
VCL (ECCV2020) [Paper] [Code]
ACP (ECCV2020) [Paper] [Code]
ConsNet (ACMMM2020) [Paper] [Code], HICO-DET Python API: A general Python toolkit for the HICO-DET dataset, including APIs for data loading & processing, human-object pair IoU & NMS calculation, and standard evaluation. [Code] [Documentation]
Action-Guided Attention Mining and Relation Reasoning Network for Human-Object Interaction Detection (IJCAI2020) [Paper]
PaStaNet (CVPR2020) [Code] [Data] [Paper] [YouTube] [bilibili]
DJ-RN (CVPR2020) [Code] [Paper]
Cascaded Human-Object Interaction Recognition (CVPR2020) [Code] [Paper]
PPDM (CVPR2020) [Code] [Paper]
IP-Net (CVPR2020) [Code] [Paper]
VSGNet (CVPR2020) [Code] [Paper]
HOID (CVPR2020) [Code] [Paper]
Diagnosing Rarity in Human-Object Interaction Detection (CVPRW2020) [Paper]
MLCNet (ICMR2020) [Paper]
SIGN (ICME2020) [Paper]
In-GraphNet (IJCAI-PRICAI 2020) [Paper]
PMFNet(ICCV2019) [Code] [Paper]
No-Frills (ICCV2019) [Code] [Paper]
Analogy (ICCV2019) [Code] [Paper]
RPNN (ICCV2019) [Paper]
Deep Contextual Attention for Human-Object Interaction Detection (ICCV2019) [Paper]
Interactiveness (CVPR2019) [Code] [Paper]
Turbo (AAAI2019) [Paper]
GPNN (ECCV2018) [Code] [Paper]
iCAN (BMVC2018) [Code] [Paper]
InteractNet (CVPR2018) [Paper]
Scaling Human-Object Interaction Recognition through Zero-Shot Learning (WACV2018) [Paper]
HO-RCNN (WACV2018) [Code] [Paper]
VS-GATs (Mar. 2020) [Paper]
Classifying All Interacting Pairs in a Single Shot (Jan. 2020) [Paper]
Novel Human-Object Interaction Detection via Adversarial Domain Generalization (May. 2020) [Paper]
PMN (Jul. 2020) [Paper] [Code]
SAG (Dec 2020) [Paper] [Code]
SABRA (Dec 2020) [Paper]

More...

Unseen or zero/low-shot or weakly-supervised learning (instance-level detection).

HOIGen (ACM MM 2024), [Paper], [Code]
CMD-SE (arXiv 2024), [Paper], [Code]
CLIP4HOI (NeurIPS 2023), [Paper]
UniHOI (NeurIPS 2023), [Paper], [Code]
Lu et. al. (arXiv 2023), [Paper], [Code]
CDT (TNNLS 2023), [Paper]
RLIPv2 (ICCV 2023), [Paper], [Code]
Unal et.al. (arXiv 2023), [Paper]
RLIP (NeurIPS 2022), [Paper], [Code]
THID (CVPR 2022), [Paper], [Code]
EoID (arXiv 2022), [Paper], [Code]
SCL (arXiv 2022), [Paper], [Code]
(CVPR 2022), [Paper], [Code]
OC-Immunity (AAAI 2022), [Paper], [Code]
Align-Former (BMVC 2021), [Paper]
CHOID (ICCV2021) [Paper], [Code]
DGIG-Net (TOC2021) [Paper]
ATL (CVPR2021) [Paper], [Code]
FCL (CVPR2021) [Paper], [Code]
Detecting Human-Object Interaction with Mixed Supervision ( 2021) [Paper]
ConsNet (ACMMM2020) [Paper] [Code]
Zero-Shot Human-Object Interaction Recognition via Affordance Graphs (Sep. 2020) [Paper]
VCL (ECCV2020) [Paper] [Code]
HOID (CVPR2020) [Code] [Paper]
Novel Human-Object Interaction Detection via Adversarial Domain Generalization (May. 2020) [Paper]
Analogy (ICCV2019) [Code] [Paper]
Functional (AAAI2020) [Paper]
Scaling Human-Object Interaction Recognition through Zero-Shot Learning (2018) [Paper]

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Video HOI methods

SPDTP (arXiv, Jun 2022), [Paper]
V-HOI (arXiv, Jun 2022), [Paper]
Detecting Human-Object Relationships in Videos (ICCV2021) [Paper]
STIGPN (Aug 2021), [Paper], [Code]
VidHOI (May 2021), [Paper]
LIGHTEN (ACMMM2020) [Paper] [Code]
Generating Videos of Zero-Shot Compositions of Actions and Objects (Jul 2020), HOI GAN, [Paper]
Grounded Human-Object Interaction Hotspots from Video (ICCV2019) [Code] [Paper]
GPNN (ECCV2018) [Code] [Paper]

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3D HOI Reconstruction/Generation/Understanding

P3HAOI (AAAI 2024) [Paper], [Project]
IM-HOI (arXiv 2023) [Paper], [Project]
Ins-HOI (arXiv 2023) [Paper], [Project]
HDM (arXiv 2023) [Paper], [Project]
HOI-Diff (arXiv 2023) [Paper], [Project]
CHOIS (arXiv 2023) [Paper], [Project]
MOB (arXiv 2023) [Paper], [Project]
PhysHOI (arXiv 2023) [Paper], [Project]
physfullbody-grasp (3DV 2024) [Paper], [Project]
MIME (CVPR 2023) [Paper], [Project]
TOHO (arXiv 2023) [Paper]
GenZI (arXiv 2023) [Paper], [Project]
CG-HOI (arXiv 2023) [Paper], [Project]
OMOMO (TOG 2023) [Paper]
HOPS (arXiv 2023) [Paper], [Project]
UniHSI (arXiv 2023) [Paper], [Project]
NIFTY (arXiv 2023) [Paper], [Project]
IMoS (EUROGRAPHICS 2023) [Paper], [Project]
SceneDiffuser (arXiv 2023) [Paper], [Project]
Locomotion-Action-Manipulation (ICCV 2023) [Paper], [Porject]
ROAM (arXiv 2023) [Paper], [Project]
Object pop-up (CVPR 2023) [Paper], [Code]
StackFLOW (IJCAI 2023) [Paper], [Code]
InterDiff (ICCV2023) [Paper], [Project]
Wang et. al. (arXiv 2022) [Paper]
Haresh et. al. (3DV 2022) [Paper], [Project]
COUCH (arXiv 2022) [Paper], [Project]
HULC (ECCV 2022) [Paper], [Project]
AROS (arXiv 2022) [Paper]
MoCapDeform (arXiv 2022) [Paper]
SUMMON (SIGGRAPH Asia 2022) [Paper], [Project]
HUMANISE (arXiv 2022) [Paper], [Project]
CHAIRS (arXiv 2022) [Paper], [Project]
NeuralDome (arXiv 2022) [Paper]
ARCTIC (arXiv 2022) [Paper], [Project]
IMoS (EUROGRAPHICS 2023) [Paper]
COINS (ECCV 2022) [Paper], [Project]
Pose2Room (ECCV 2022) [Paper], [Project]
RICH (CVPR 2022) [Paper], [Project]
MOVER (CVPR 2022) [Paper], [Project]
SAGA (ECCV 2022) [Paper], [Project]
GOAL (CVPR 2022) [Paper], [Project]
BEHAVE (CVPR 2022) [Paper], [Project]
CHORE (ECCV 2022) [Project], [Paper]
POSA (CVPR 2021) [Paper], [Project]
GraviCap (ICCV 2021) [Paper], [Project]
D3D-HOI (arXiv 2021) [Paper], [Project]
PSI (CVPR 2020) [Paper], [Code]
DJ-RN (CVPR 2020) [Paper], [Code]
PLACE (3DV 2020) [Paper], [Project]
GRAB (ECCV 2020) [Paper], [Project]
Holistic++ (ICCV 2019) [Paper], [[Code]]()
PROX (ICCV 2019) [Paper], [Project]

Result

PaStaNet-HOI:

Proposed by TIN (TPAMI version, Transferable Interactiveness Network). It is built on HAKE data, includes 110K+ images and 520 HOIs (without the 80 "no_interaction" HOIs of HICO-DET to avoid the incomplete labeling). It has a more severe long-tailed data distribution thus is more difficult.

Detector: COCO pre-trained

Method	mAP
iCAN	11.00
iCAN+NIS	13.13
TIN	15.38

HICO-DET:

1) Detector: COCO pre-trained

Method	Pub	Full(def)	Rare(def)	None-Rare(def)	Full(ko)	Rare(ko)	None-Rare(ko)
Shen et al.	WACV2018	6.46	4.24	7.12	-	-	-
HO-RCNN	WACV2018	7.81	5.37	8.54	10.41	8.94	10.85
InteractNet	CVPR2018	9.94	7.16	10.77	-	-	-
Turbo	AAAI2019	11.40	7.30	12.60	-	-	-
GPNN	ECCV2018	13.11	9.34	14.23	-	-	-
Xu et. al	ICCV2019	14.70	13.26	15.13	-	-	-
iCAN	BMVC2018	14.84	10.45	16.15	16.26	11.33	17.73
Wang et. al.	ICCV2019	16.24	11.16	17.75	17.73	12.78	19.21
Lin et. al	IJCAI2020	16.63	11.30	18.22	19.22	14.56	20.61
Functional (suppl)	AAAI2020	16.96	11.73	18.52	-	-	-
Interactiveness	CVPR2019	17.03	13.42	18.11	19.17	15.51	20.26
No-Frills	ICCV2019	17.18	12.17	18.68	-	-	-
RPNN	ICCV2019	17.35	12.78	18.71	-	-	-
PMFNet	ICCV2019	17.46	15.65	18.00	20.34	17.47	21.20
SIGN	ICME2020	17.51	15.31	18.53	20.49	17.53	21.51
Interactiveness-optimized	CVPR2019	17.54	13.80	18.65	19.75	15.70	20.96
Liu et.al.	arXiv	17.55	20.61	-	-	-	-
Wang et al.	ECCV2020	17.57	16.85	17.78	21.00	20.74	21.08
UnionDet	arXiv2023	17.58	11.72	19.33	19.76	14.68	21.27
In-GraphNet	IJCAI-PRICAI 2020	17.72	12.93	19.31	-	-	-
HOID	CVPR2020	17.85	12.85	19.34	-	-	-
MLCNet	ICMR2020	17.95	16.62	18.35	22.28	20.73	22.74
SAG	arXiv	18.26	13.40	19.71	-	-	-
Sarullo et al.	arXiv	18.74	-	-	-	-	-
DRG	ECCV2020	19.26	17.74	19.71	23.40	21.75	23.89
Analogy	ICCV2019	19.40	14.60	20.90	-	-	-
VCL	ECCV2020	19.43	16.55	20.29	22.00	19.09	22.87
VS-GATs	arXiv	19.66	15.79	20.81	-	-	-
VSGNet	CVPR2020	19.80	16.05	20.91	-	-	-
PFNet	CVM	20.05	16.66	21.07	24.01	21.09	24.89
ATL(w/ COCO)	CVPR2021	20.08	15.57	21.43	-	-	-
FCMNet	ECCV2020	20.41	17.34	21.56	22.04	18.97	23.12
ACP	ECCV2020	20.59	15.92	21.98	-	-	-
PD-Net	ECCV2020	20.81	15.90	22.28	24.78	18.88	26.54
SG2HOI	ICCV2021	20.93	18.24	21.78	24.83	20.52	25.32
TIN-PAMI	TAPMI2021	20.93	18.95	21.32	23.02	20.96	23.42
ATL	CVPR2021	21.07	16.79	22.35	-	-	-
PMN	arXiv	21.21	17.60	22.29	-	-	-
IPGN	TIP2021	21.26	18.47	22.07	-	-	-
DJ-RN	CVPR2020	21.34	18.53	22.18	23.69	20.64	24.60
OSGNet	IEEE Access	21.40	18.12	22.38	-	-	-
K-BAN	arXiv2022	21.48	16.85	22.86	24.29	19.09	25.85
SCG+ODM	ECCV2022	21.50	17.59	22.67	-	-	-
DIRV	AAAI2021	21.78	16.38	23.39	25.52	20.84	26.92
SCG	ICCV2021	21.85	18.11	22.97	-	-	-
HRNet	TIP2021	21.93	16.30	23.62	25.22	18.75	27.15
ConsNet	ACMMM2020	22.15	17.55	23.52	26.57	20.8	28.3
SKGHOI	arXiv2023	22.61	15.87	24.62	-	-	-
IDN	NeurIPS2020	23.36	22.47	23.63	26.43	25.01	26.85
QAHOI-Res50	arXiv2021	24.35	16.18	26.80	-	-	-
DOQ	CVPR2022	25.97	26.09	25.93	-	-	-
STIP	CVPR2022	28.81	27.55	29.18	32.28	31.07	32.64

2) Detector: pre-trained on COCO, fine-tuned on HICO-DET train set (with GT human-object pair boxes) or one-stage detector (point-based, transformer-based)

The finetuned detector would learn to only detect the interactive humans and objects (with interactiveness), thus suppressing many wrong pairings (non-interactive human-object pairs) and boosting the performance.	Method	Pub	Full(def)	Rare(def)	None-Rare(def)	Full(ko)	Rare(ko)
UniDet	ECCV2020	17.58	11.72	19.33	19.76	14.68	21.27
IP-Net	CVPR2020	19.56	12.79	21.58	22.05	15.77	23.92
RR-Net	arXiv	20.72	13.21	22.97	-	-	-
PPDM (paper)	CVPR2020	21.10	14.46	23.09	-	-	-
PPDM (github-hourglass104)	CVPR2020	21.73/21.94	13.78/13.97	24.10/24.32	24.58/24.81	16.65/17.09	26.84/27.12
Functional	AAAI2020	21.96	16.43	23.62	-	-	-
SABRA-Res50	arXiv	23.48	16.39	25.59	28.79	22.75	30.54
VCL	ECCV2020	23.63	17.21	25.55	25.98	19.12	28.03
ATL	CVPR2021	23.67	17.64	25.47	26.01	19.60	27.93
PST	ICCV2021	23.93	14.98	26.60	26.42	17.61	29.05
SABRA-Res50FPN	arXiv	24.12	15.91	26.57	29.65	22.92	31.65
ATL(w/ COCO)	CVPR2021	24.50	18.53	26.28	27.23	21.27	29.00
IDN	NeurIPS2020	24.58	20.33	25.86	27.89	23.64	29.16
FCL	CVPR2021	24.68	20.03	26.07	26.80	21.61	28.35
HOTR	CVPR2021	25.10	17.34	27.42	-	-	-
FCL+VCL	CVPR2021	25.27	20.57	26.67	27.71	22.34	28.93
OC-Immunity	AAAI2022	25.44	23.03	26.16	27.24	24.32	28.11
ConsNet-F	ACMMM2020	25.94	19.35	27.91	30.34	23.4	32.41
SABRA-Res152	arXiv	26.09	16.29	29.02	31.08	23.44	33.37
QAHOI-Res50	arXiv2021	26.18	18.06	28.61	-	-	-
Zou et al.	CVPR2021	26.61	19.15	28.84	29.13	20.98	31.57
SKGHOI	arXiv2023	26.95	21.28	28.56	-	-	-
RGBM	arXiv2022	27.39	21.34	29.20	30.87	24.20	32.87
GTNet	arXiv	28.03	22.73	29.61	29.98	24.13	31.73
K-BAN	arXiv2022	28.83	20.29	31.31	31.05	21.41	33.93
AS-Net	CVPR2021	28.87	24.25	30.25	31.74	27.07	33.14
QPIC-Res50	CVPR2021	29.07	21.85	31.23	31.68	24.14	33.93
GGNet	CVPR2021	29.17	22.13	30.84	33.50	26.67	34.89
QPIC-CPC	CVPR2022	29.63	23.14	31.57	-	-	-
QPIC-Res101	CVPR2021	29.90	23.92	31.69	32.38	26.06	34.27
SCG	ICCV2021	29.26	24.61	30.65	32.87	27.89	34.35
MHOI	TCSVT2022	29.67	24.37	31.25	31.87	27.28	33.24
PhraseHOI	AAAI2022	30.03	23.48	31.99	33.74	27.35	35.64
CDT	TNNLS 2023	30.48	25.48	32.37	-	-	-
SQAB	Displays2023	30.82	24.92	32.58	33.58	27.19	35.49
MSTR	CVPR2022	31.17	25.31	32.92	34.02	28.83	35.57
SSRT	CVPR2022	31.34	24.31	33.32	-	-	-
OCN	AAAI2022	31.43	25.80	33.11	-	-	-
SCG+ODM	ECCV2022	31.65	24.95	33.65	-	-	-
DT	CVPR2022	31.75	27.45	33.03	34.50	30.13	35.81
ParSe (COCO)	NeurIPS2022	31.79	26.36	33.41	-	-	-
CATN (w/ Bert)	CVPR2022	31.86	25.15	33.84	34.44	27.69	36.45
SQA	ICASSP2023	31.99	29.88	32.62	35.12	32.74	35.84
CDN	NeurIPS2021	32.07	27.19	33.53	34.79	29.48	36.38
STIP	CVPR2022	32.22	28.15	33.43	35.29	31.43	36.45
DEFR	arXiv2021	32.35	33.45	32.02	-	-	-
PQNet-L	mmasia2022	32.45	27.80	33.84	35.28	30.72	36.64
CDN-s+HQM	ECCV2022	32.47	28.15	33.76	-	-	-
UPT	CVPR2022	32.62	28.62	33.81	36.08	31.41	37.47
OpenCat	CVPR2023	32.68	28.42	33.75	-	-	-
Iwin	ECCV2022	32.79	27.84	35.40	35.84	28.74	36.09
RLIP-ParSe (VG+COCO)	NeurIPS2022	32.84	26.85	34.63	-	-	-
PR-Net	arXiv2023	32.86	28.03	34.30	-	-	-
MUREN	CVPR2023	32.87	28.67	34.12	35.52	30.88	36.91
SDT	arXiv2022	32.97	28.49	34.31	36.32	31.90	37.64
HODN	TMM2023	33.14	28.54	34.52	35.86	31.18	37.26
SG2HOI	arxXiv2023	33.14	29.27	35.72	35.73	32.01	36.43
PDN	PR2023	33.18	27.95	34.75	35.86	30.57	37.43
DOQ	CVPR2022	33.28	29.19	34.50	-	-	-
IF	CVPR2022	33.51	30.30	34.46	36.28	33.16	37.21
ICDT	ICANN2023	34.01	27.60	35.92	36.29	29.88	38.21
PSN	arXiv2023	34.02	29.44	35.39	-	-	-
KI2HOI	arXiv2024	34.20	32.26	36.10	37.85	35.89	38.78
VIL+	ACMMM2023	34.21	30.58	35.30	37.67	34.88	38.50
Multi-Step	ACMMM2023	34.42	30.03	35.73	37.71	33.74	38.89
OBPA-Net	PRCV2023	34.63	32.83	35.16	36.78	35.38	38.04
MLKD	WACV2024	34.69	31.12	35.74	-	-	-
HOICLIP	CVPR2023	34.69	31.12	35.74	37.61	34.47	38.54
PViC w/ detr	ICCV2023	34.69	32.14	35.45	38.14	35.38	38.97
GEN-VLKT+SCA	arXiv2023	34.79	31.80	35.68	-	-	-
HOIGen	ACMMM2024	34.84	34.52	34.94	-	-	-
SBM	PRCV2023	34.92	31.67	35.85	38.79	35.43	39.60
(w/ CLIP)	CVPR2022	34.95	31.18	36.08	38.22	34.36	39.37
SOV-STG (res101)	arXiv2023	35.01	30.63	36.32	37.60	32.77	39.05
GeoHOI	arXiv2024	35.05	33.01	35.71	37.12	34.79	37.97
PartMap	ECCV2022	35.15	33.71	35.58	37.56	35.87	38.06
GFIN	NN2023	35.28	31.91	36.29	38.80	35.48	39.79
CLIP4HOI	NeurIPS2023	35.33	33.95	35.74	37.19	35.27	37.77
LOGICHOI	NeurIPS2023	35.47	32.03	36.22	38.21	35.29	39.03
QAHOI-Swin-Large-ImageNet-22K	arXiv2021	35.78	29.80	37.56	37.59	31.66	39.36
DPADN	AAAI2024	35.91	35.82	35.94	38.99	39.61	38.80
-L + CQL	CVPR2023	36.03	33.16	36.89	38.82	35.51	39.81
HOICLIP+DP-HOI	CVPR2024	36.56	34.36	37.22	-	-	-
AGER	ICCV2023	36.75	33.53	37.71	39.84	35.58	40.23
FGAHOI	arXiv2023	37.18	30.71	39.11	38.93	31.93	41.02
ViPLO	CVPR2023	37.22	35.45	37.75	40.61	38.82	41.15
RmLR	ICCV2023	37.41	28.81	39.97	38.69	31.27	40.91
HCVC	arXiv2023	37.54	37.01	37.78	39.98	39.01	40.32
ADA-CM	ICCV2023	38.40	37.52	38.66	-	-	-
UniVRD w/ extra data+VLM	arXiv2023	38.61	33.39	40.16	-	-	-
SCTC	AAAI2024	39.12	36.09	39.87	-	-	-
BCOM	CVPR2024	39.34	39.90	39.17	42.24	42.86	42.05
UniHOI	NeurIPS2023	40.95	40.27	41.32	43.26	43.12	43.25
DiffHOI w/ syn data	arXiv2023	41.50	39.96	41.96	43.62	41.41	44.28
DiffusionHOI	NeurIPS2024	42.54	42.95	42.35	44.91	45.18	44.83
SOV-STG (swin-l)	arXiv2023	43.35	42.25	43.69	45.53	43.62	46.11
PViC w/ h-detr (swin-l)	ICCV2023	44.32	44.61	44.24	47.81	48.38	47.64
MP-HOI	CVPR2024	44.53	44.48	44.55	-	-	-
SICHOI	CVPR2024	45.04	45.61	44.88	48.16	48.37	48.09
RLIPv2-ParSeDA w/ extra data	ICCV2023	45.09	43.23	45.64	-	-	-
CycleHOI	arXiv2024	45.71	46.14	45.52	49.23	49.87	48.96
Pose-Aware	CVPR2024	46.01	46.74	45.80	49.50	50.59	49.18

3) Ground Truth human-object pair boxes (only evaluating HOI recognition)

Method	Pub	Full(def)	Rare(def)	None-Rare(def)
iCAN	BMVC2018	33.38	21.43	36.95
Interactiveness	CVPR2019	34.26	22.90	37.65
Analogy	ICCV2019	34.35	27.57	36.38
ATL	CVPR2021	43.32	33.84	46.15
IDN	NeurIPS2020	43.98	40.27	45.09
ATL(w/ COCO)	CVPR2021	44.27	35.52	46.89
FCL	CVPR2021	45.25	36.27	47.94
GTNet	arXiv	46.45	35.10	49.84
SCG	ICCV2021	51.53	41.01	54.67
K-BAN	arXiv2022	52.99	34.91	58.40
ConsNet	ACMMM2020	53.04	38.79	57.3
ViPLO	CVPR2023	62.09	59.26	62.93

4) Interactiveness detection (interactive or not + pair box detection):

Method	Pub	HICO-DET	V-COCO
TIN++	TPAMI2022	14.35	29.36
PPDM	CVPR2020	27.34	-
QPIC	CVPR2021	32.96	38.33
CDN	NeurIPS2021	33.55	40.13
PartMap	ECCV2022	38.74	43.61

5) Enhanced with HAKE:

Method	Pub	Full(def)	Rare(def)	None-Rare(def)	Full(ko)	Rare(ko)	None-Rare(ko)
iCAN	BMVC2018	14.84	10.45	16.15	16.26	11.33	17.73
iCAN + HAKE-HICO-DET	CVPR2020	19.61 (+4.77)	17.29	20.30	22.10	20.46	22.59
Interactiveness	CVPR2019	17.03	13.42	18.11	19.17	15.51	20.26
Interactiveness + HAKE-HICO-DET	CVPR2020	22.12 (+5.09)	20.19	22.69	24.06	22.19	24.62
Interactiveness + HAKE-Large	CVPR2020	22.66 (+5.63)	21.17	23.09	24.53	23.00	24.99

6) Zero-Shot HOI detection:

Unseen action-object combination scenario (UC)

Method	Pub	Detector	Unseen(def)	Seen(def)	Full(def)
Shen et al.	WACV2018	COCO	5.62	-	6.26
Functional	AAAI2020	HICO-DET	11.31 ± 1.03	12.74 ± 0.34	12.45 ± 0.16
ConsNet	ACMMM2020	COCO	16.99 ± 1.67	20.51 ± 0.62	19.81 ± 0.32
CDT	TNNLS 2023	-	18.06	23.34	20.72
EoID	AAAI2023	-	23.01±1.54	30.39±0.40	28.91±0.27
HOICLIP	CVPR2023	-	25.53	34.85	32.99
KI2HOI	arXiv2024	-	27.43	35.76	34.56
CLIP4HOI	NeurIPS2023	-	27.71	33.25	32.11
HOIGen	ACMMM2024	-	30.26	34.23	33.44
VCL (NF-UC)	ECCV2020	HICO-DET	16.22	18.52	18.06
ATL(w/ COCO) ((NF-UC))	CVPR2021	HICO-DET	18.25	18.78	18.67
FCL (NF-UC)	CVPR2021	HICO-DET	18.66	19.55	19.37
RLIP-ParSe (NF-UC)	NeurIPS2022	COCO, VG	20.27	27.67	26.19
SCL	arxiv	HICO-DET	21.73	25.00	24.34
OpenCat(NF-UC)	CVPR2023	HICO-DET	23.25	28.04	27.08
GEN-VLKT* (NF-UC)	CVPR2022	HICO-DET	25.05	23.38	23.71
EoID (NF-UC)	AAAI2023	HICO-DET	26.77	26.66	26.69
HOICLIP (NF-UC)	CVPR2023	HICO-DET	26.39	28.10	27.75
LOGICHOI (NF-UC)	NeurIPS2023	-	26.84	27.86	27.95
Wu et.al. (NF-UC)	AAAI2024	-	27.35	22.09	23.14
UniHOI (NF-UC)	NeurIPS2023	-	28.45	32.63	31.79
KI2HOI (NF-UC)	arXiv2024	-	28.89	28.31	27.77
DiffHOI w/ syn data (NF-UC)	arXiv2023	HICO-DET + syn data	29.45	31.68	31.24
HCVC (NF-UC)	arXiv2023	-	28.44	31.35	30.77
CLIP4HOI (NF-UC)	NeurIPS2023	-	31.44	28.26	28.90
HOIGen (NF-UC)	ACMMM2024	-	33.98	32.86	33.08
VCL (RF-UC)	ECCV2020	HICO-DET	10.06	24.28	21.43
ATL(w/ COCO) ((RF-UC))	CVPR2021	HICO-DET	9.18	24.67	21.57
FCL (RF-UC)	CVPR2021	HICO-DET	13.16	24.23	22.01
SCL (RF-UC)	arxiv	HICO-DET	19.07	30.39	28.08
RLIP-ParSe (RF-UC)	NeurIPS2022	COCO, VG	19.19	33.35	30.52
GEN-VLKT* (RF-UC)	CVPR2022	HICO-DET	21.36	32.91	30.56
OpenCat(RF-UC)	CVPR2023	HICO-DET	21.46	33.86	31.38
Wu et.al. (RF-UC)	AAAI2024	-	23.32	30.09	28.53
HOICLIP (RF-UC)	CVPR2023	HICO-DET	25.53	34.85	32.99
LOGICHOI (RF-UC)	NeurIPS2023	-	25.97	34.93	33.17
KI2HOI (RF-UC)	arXiv2024	-	26.33	35.79	34.10
CLIP4HOI	NeurIPS2023	-	28.47	35.48	34.08
UniHOI (RF-UC)	NeurIPS2023	-	28.68	33.16	32.27
DiffHOI w/ syn data (RF-UC)	arXiv2023	HICO-DET + syn data	28.76	38.01	36.16
HCVC (RF-UC)	arXiv2023	-	30.95	37.16	35.87
HOIGen (RF-UC)	ACMMM2024	-	31.01	34.57	33.86
RLIPv2-ParSeDA (RF-UC)	ICCV2023	VG, COCO, O365	31.23	45.01	42.26

* indicates large Visual-Language model pretraining, \eg, CLIP.
For the details of the setting, please refer to corresponding publications. This is not officially published and might miss some publications. Please find the corresponding publications.

Zero-shot* HOI detection without fine-tuning (NF)

Method	Pub	Backbone	Dataset	Detector	Full	Rare	Non-Rare
RLIP-ParSeD	NeurIPS2022	ResNet-50	COCO + VG	DDETR	13.92	11.20	14.73
RLIP-ParSe	NeurIPS2022	ResNet-50	COCO + VG	DETR	15.40	15.08	15.50
RLIPv2-ParSeDA	ICCV2023	Swin-L	VG+COCO+O365	DDETR	23.29	27.97	21.90

* indicates a formulation that assesses the generalization of a pre-training model to unseen distributions, proposed in RLIP. zero-shot follows the terminology from CLIP.

Unseen object scenario (UO)

Method	Pub	Detector	Full(def)	Seen(def)	Unseen(def)
Functional	AAAI2020	HICO-DET	13.84	14.36	11.22
FCL	CVPR2021	HICO-DET	19.87	20.74	15.54
ConsNet	ACMMM2020	COCO	20.71	20.99	19.27
Wu et.al.	AAAI2024	-	27.73	27.87	27.05
ATL	CVPR2021	-	15.11	21.54	20.47
GEN-VLKT	CVPR2022	-	10.51	28.92	25.63
LOGICHOI	NeurIPS2023	-	15.67	30.42	28.23
HOICLIP	CVPR2023	-	16.20	30.99	28.53
KI2HOI	arXiv2024	-	16.50	31.70	28.84
HCVC	arXiv2023	-	16.78	33.31	30.53
CLIP4HOI	NeurIPS2023	-	31.79	32.73	32.58
HOIGen	ACMMM2024	-	36.35	32.90	33.48

Unseen action scenario (UA)

Method	Pub	Detector	Full(def)	Seen(def)	Unseen(def)
ConsNet	ACMMM2020	COCO	19.04	20.02	14.12
CDT	TNNLS 2023	-	19.68	21.45	15.17
Wu et.al.	AAAI2024	-	26.43	28.13	17.92
EoID	AAAI2023	-	29.22	30.46	23.04

Unseen action scenario (UV), results from EoID

Method	Pub	Detector	Unseen(def)	Seen(def)	Full(def)
HOIGen	ACMMM2024	-	20.27	34.31	32.34
GEN-VLKT	CVPR2022	-	20.96	30.23	28.74
EoID	AAAI2023	-	22.71	30.73	29.61
HOICLIP	CVPR2023	-	24.30	32.19	31.09
LOGICHOI	NeurIPS2023	-	24.57	31.88	30.77
HCVC	arXiv2023	-	24.69	36.11	34.51
KI2HOI	arXiv2024	-	25.20	32.95	31.85
CLIP4HOI	NeurIPS2023	-	26.02	31.14	30.42
UniHOI	NeurIPS2023	-	26.05	36.78	34.68

Another setting

Method	Pub	Unseen	Seen	Full
Shen et. al.	WACV2018	5.62	-	6.26
Functional	AAAI2020	10.93	12.60	12.26
VCL	ECCV2020	10.06	24.28	21.43
ATL	CVPR2021	9.18	24.67	21.57
FCL	CVPR2021	13.16	24.23	22.01
THID (w/ CLIP)	CVPR2022	15.53	24.32	22.96
EoID	AAAI2023	22.04	31.39	29.52
GEN-VLKT	CVPR2022	21.36	32.91	30.56

7) Few-Shot HOI detection:

1% HICO-Det Data used in fine-tuning

Method	Pub	Backbone	Dataset	Detector	Data	Full	Rare	Non-Rare
RLIP-ParSeD	NeurIPS2022	ResNet-50	COCO + VG	DDETR	1%	18.30	16.22	18.92
RLIP-ParSe	NeurIPS2022	ResNet-50	COCO + VG	DETR	1%	18.46	17.47	18.76
RLIPv2-ParSeDA	ICCV2023	Swin-L	VG+COCO+O365	DDETR	1%	32.22	31.89	32.32

10% HICO-Det Data used in fine-tuning

Method	Pub	Backbone	Dataset	Detector	Data	Full	Rare	Non-Rare
RLIP-ParSeD	NeurIPS2022	ResNet-50	COCO + VG	DDETR	10%	22.09	15.89	23.94
RLIP-ParSe	NeurIPS2022	ResNet-50	COCO + VG	DETR	10%	22.59	20.16	23.32
RLIPv2-ParSeDA	ICCV2023	Swin-L	VG+COCO+O365	DDETR	10%	37.46	34.75	38.27

8) Weakly-supervised HOI detection:

Method	Pub	Backbone	Dataset	Detector	Full	Rare	Non-Rare
Explanation-HOI	ECCV2020	ResNeXt101	COCO	FRCNN	10.63	8.71	11.20
MX-HOI	WACV2021	ResNet-101	COCO	FRCNN	16.14	12.06	17.50
PPR-FCN (from Weakly-HOI-CLIP)	ICCV2017	ResNet-50, CLIP	COCO	FRCNN	17.55	15.69	18.41
Align-Former	BMVC2021	ResNet-101	-	-	20.85	18.23	21.64
Weakly-HOI-CLIP	ICLR2023	ResNet-101, CLIP	COCO	FRCNN	25.70	24.52	26.05
OpenCat	CVPR 2023	DETR	-	-	25.82	24.35	26.19

Ambiguous-HOI

Detector: COCO pre-trained

Method	mAP
iCAN	8.14
Interactiveness	8.22
Analogy(reproduced)	9.72
DJ-RN	10.37
OC-Immunity	10.45

SWiG-HOI

Method	Pub	Non-Rare	Unseen	Seen	Full
JSR	ECCV2020	10.01	6.10	2.34	6.08
CHOID	ICCV2021	10.93	6.63	2.64	6.64
QPIC	CVPR2021	16.95	10.84	6.21	11.12
THID (w/ CLIP)	CVPR2022	17.67	12.82	10.04	13.26

V-COCO: Scenario1

1) Detector: COCO pre-trained or one-stage detector

Method	Pub	AP(role)
Gupta et al.	arXiv	31.8
InteractNet	CVPR2018	40.0
Turbo	AAAI2019	42.0
GPNN	ECCV2018	44.0
UniVRD w/ extra data+VLM	arXiv2023	45.19
iCAN	BMVC2018	45.3
Xu et. al	CVPR2019	45.9
Wang et. al.	ICCV2019	47.3
UniDet	ECCV2020	47.5
Interactiveness	CVPR2019	47.8
Lin et. al	IJCAI2020	48.1
VCL	ECCV2020	48.3
Zhou et. al.	CVPR2020	48.9
In-GraphNet	IJCAI-PRICAI 2020	48.9
Interactiveness-optimized	CVPR2019	49.0
TIN-PAMI	TAPMI2021	49.1
IP-Net	CVPR2020	51.0
DRG	ECCV2020	51.0
RGBM	arXiv2022	51.7
VSGNet	CVPR2020	51.8
PMN	arXiv	51.8
PMFNet	ICCV2019	52.0
Liu et.al.	arXiv	52.28
FCL	CVPR2021	52.35
PD-Net	ECCV2020	52.6
Wang et.al.	ECCV2020	52.7
PFNet	CVM	52.8
Zou et al.	CVPR2021	52.9
SIGN	ICME2020	53.1
ACP	ECCV2020	52.98 (53.23)
FCMNet	ECCV2020	53.1
HRNet	TIP2021	53.1
SGCN4HOI	IEEESMC2022	53.1
ConsNet	ACMMM2020	53.2
IDN	NeurIPS2020	53.3
SG2HOI	ICCV2021	53.3
OSGNet	IEEE Access	53.43
SABRA-Res50	arXiv	53.57
K-BAN	arXiv2022	53.70
IPGN	TIP2021	53.79
AS-Net	CVPR2021	53.9
RR-Net	arXiv	54.2
SCG	ICCV2021	54.2
HOKEM	arXiv2023	54.6
SABRA-Res50FPN	arXiv	54.69
GGNet	CVPR2021	54.7
MLCNet	ICMR2020	55.2
HOTR	CVPR2021	55.2
DIRV	AAAI2021	56.1
UnionDet	arXiv2023	56.2
SABRA-Res152	arXiv	56.62
PhraseHOI	AAAI2022	57.4
GTNet	arXiv	58.29
QPIC-Res101	CVPR2021	58.3
ADA-CM	ICCV2023	58.57
QPIC-Res50	CVPR2021	58.8
ICDT	ICANN2023	59.4
CATN (w/ fastText)	CVPR2022	60.1
FGAHOI	arXiv2023	60.5
Iwin	ECCV2022	60.85
UPT-ResNet-101-DC5	CVPR2022	61.3
CDT	TNNLS 2023	61.43
SBM	PRCV2023	61.5
SDT	arXiv2022	61.8
OpenCat	CVPR2023	61.9
MSTR	CVPR2022	62.0
ViPLO	CVPR2023	62.2
Multi-Step	ACMMM2023	62.4
PViC w/ detr	ICCV2023	62.8
PR-Net	arXiv2023	62.9
IF	CVPR2022	63.0
ParMap	ECCV2022	63.0
QPIC-CPC	CVPR2022	63.1
DOQ	CVPR2022	63.5
HOICLIP	CVPR2023	63.5
GEN-VLKT (w/ CLIP)	CVPR2022	63.58
SG2HOI	arxXiv2023	63.6
QPIC+HQM	ECCV2022	63.6
SOV-STG	arXiv2023	63.9
KI2HOI	arXiv2024	63.9
CDN	NeurIPS2021	63.91
PViC w/ h-detr (swin-l)	ICCV2023	64.1
OBPA-Net	PRCV2023	64.1
RmLR	ICCV2023	64.17
RLIP-ParSe (COCO+VG)	NeurIPS2022	64.2
LOGICHOI	NeurIPS2023	64.4
MHOI	TCSVT2022	64.5
GEN-VLKT+SCA	arXiv2023	64.5
PDN	PR2023	64.7
ParSe (COCO)	NeurIPS2022	64.8
SSRT	CVPR2022	65.0
SQAB	Displays2023	65.0
OCN	AAAI2022	65.3
SQA	ICASSP2023	65.4
AGER	ICCV2023	65.68
DiffHOI	arXiv2023	65.7
BCOM	CVPR2024	65.8
PSN	arXiv2023	65.9
DPADN	AAAI2024	62.62
Pose-Aware	CVPR2024	63.0
CO-HOI	arXiv2024	65.44
STIP	CVPR2022	66.0
DT	CVPR2022	66.2
MP-HOI	CVPR2024	66.2
CLIP4HOI	NeurIPS2023	66.3
GENs+DP-HOI	CVPR2024	66.6
GEN-VLKT-L + CQL	CVPR2023	66.8
CycleHOI	arXiv2024	66.8
HODN	TMM2023	67.0
DiffusionHOI	NeurIPS2024	67.1
VIL+DisTR	ACMMM2023	67.6
UniHOI	NeurIPS2023	68.05
SCTC	AAAI2024	68.2
HCVC	arXiv2023	68.4
MUREN	CVPR2023	68.8
GeoHOI	arXiv2024	69.4
GFIN	NN2023	70.1
SICHOI	CVPR2024	71.1
RLIPv2-ParSeDA w/ extra data	ICCV2023	72.1

2) Enhanced with HAKE:

Method	Pub	AP(role)
iCAN	CVPR2019	45.3
iCAN + HAKE-Large (transfer learning)	CVPR2020	49.2 (+3.9)
Interactiveness	CVPR2019	47.8
Interactiveness + HAKE-Large (transfer learning)	CVPR2020	51.0 (+3.2)

3) Weakly-supervised HOI detection:

Method	Pub	Backbone	Dataset	Detector	AP(role)-S1	AP(role)-S2
Weakly-HOI-CLIP	ICLR2023	ResNet-101, CLIP	COCO	FRCNN	44.74	49.97

HOI-COCO:

based on V-COCO

Method	Pub	Full	Seen	Unseen
VCL	ECCV2020	23.53	8.29	35.36
ATL(w/ COCO)	CVPR2021	23.40	8.01	35.34

HICO

1) Default

Method	mAP
R*CNN	28.5
Girdhar et.al.	34.6
Mallya et.al.	36.1
RAM++ LLM	37.6
Pairwise	39.9
RelViT	40.12
DEFR-base	44.1
OpenTAP	51.7
DEFR-CLIP	60.5
HTS	60.5
DEFR/16 CLIP	65.6

2) Enhanced with HAKE:

Method	mAP
Mallya et.al.	36.1
Mallya et.al.+HAKE-HICO	45.0 (+8.9)
Pairwise	39.9
Pairwise+HAKE-HICO	45.9 (+6.0)
Pairwise+HAKE-Large	46.3 (+6.4)

DirtyHarryLYL / HOI-Learning-List

readme

HOI-Learning-List

Image Dataset/Benchmark

Video HOI Datasets

3D HOI Datasets

Survey

Method

HOI Image Generation

HOI Recognition: Image-based, to recognize all the HOIs in one image.

Unseen or zero-shot learning (image-level recognition).

HOI for Robotics.

HOI Detection: Instance-based, to detect the human-object pairs and classify the interactions.

Unseen or zero/low-shot or weakly-supervised learning (instance-level detection).

Video HOI methods

3D HOI Reconstruction/Generation/Understanding

Result

PaStaNet-HOI:

Detector: COCO pre-trained

HICO-DET:

1) Detector: COCO pre-trained

2) Detector: pre-trained on COCO, fine-tuned on HICO-DET train set (with GT human-object pair boxes) or one-stage detector (point-based, transformer-based)

3) Ground Truth human-object pair boxes (only evaluating HOI recognition)

4) Interactiveness detection (interactive or not + pair box detection):

5) Enhanced with HAKE:

6) Zero-Shot HOI detection:

Unseen action-object combination scenario (UC)

Zero-shot* HOI detection without fine-tuning (NF)

Unseen object scenario (UO)

Unseen action scenario (UA)

Unseen action scenario (UV), results from EoID

Another setting

7) Few-Shot HOI detection:

1% HICO-Det Data used in fine-tuning

10% HICO-Det Data used in fine-tuning

8) Weakly-supervised HOI detection:

Ambiguous-HOI

Detector: COCO pre-trained

SWiG-HOI

V-COCO: Scenario1

1) Detector: COCO pre-trained or one-stage detector

2) Enhanced with HAKE:

3) Weakly-supervised HOI detection:

HOI-COCO:

HICO

1) Default

2) Enhanced with HAKE: