Closed fake-warrior8 closed 1 year ago
For ActivityNet v1.3, we learn action proposals rather than the real action instances due to the optimization issue. We comine the action proposals with external action classifiers to obtain the final action predictions, if you have more question, please refer to our paper .
For ActivityNet v1.3, we learn action proposals rather than the real action instances due to the optimization issue. We comine the action proposals with external action classifiers to obtain the final action predictions, if you have more question, please refer to our paper .
I will check it. Thank you!
Hi, I want to know why you set num_classes as 1 in ActivityNet dataset module line122, which make the gold label is a trivial zero. The setting comes from anet_tsp.yaml.
dataset: { json_file: ./data/anet_1.3/annotations/anet1.3_tsp_filtered.json, feat_folder: ./data/anet_1.3/tsp_features, fileprefix: v, file_ext: .npy, num_classes: 1, input_dim: 512, feat_stride: 16, num_frames: 16, default_fps: 15, trunc_thresh: 0.5, crop_ratio: [0.9, 1.0],
upsample the features to a fixed length of 192
max_seq_len: 192, force_upsampling: True, }