Comments (2)
sallymmx
commented on July 20, 2024
temporal transformer只重在时序建模，zero-shot重点来自于前面的spatial建模和文本的特征编码。实验也表明不只是是对train data的类别好。
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gurkirt
commented on July 20, 2024
Since it has trainable parameters, how can you be sure that it only does temporal modelling?
with MeanP, I get the following results.
wandb: Run summary:
wandb: top1 0.32762
wandb: top5 3.62399
Can you please explain what is goinf on?
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Related Issues (20)
- The details about multi-label video classification (Charades)
- The checkpoints of HMDB51 & UCF101 are not found
- 关于小样本设置下的结果 HOT 4
- 转onnx HOT 1
- The links of pretrained models are expired. HOT 4
- about pretrained weights (on K400)
- Looking for help to try ActionCLIP for custom videos HOT 3
- 关于zero-shot测试和few-shot测试的设置问题 HOT 3
- About the pretrained model
- 请问能提供预处理后的数据集下载链接吗，非常感谢
- About input data- video file, prompts
- No train/validation/test list for HMDB51 or Kinetics? HOT 2
- Pretrained models from baidu?
- 您好，想知道zero-shot实验中ucf_zero_shot.yaml中label_list的csv文件中存放的哪些信息，还有val_list的txt文件存放的哪些信息
- environment.yml HOT 1
- visualized results
- 4.5. Comparison with State-of-the-art Methods The results in the appendix
- random seed HOT 1
- where is T
- Model Weights unavailable for download HOT 3
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