Comments (2)
YinRui1991
commented on September 7, 2024
@LiliMeng Hi, you can try to add attentional pooling layer to LSTM if you want to improve accuracy on action dataset, such as UCF101. I think that only CNN is not enough for action classification and RNN is good at temporal work. Attentional pooling is a good observer that you can see and show where CNNs focus on.
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rohitgirdhar
commented on September 7, 2024
Thanks for trying the experiment on UCF101. This is a little surprising as I would expect things to improve on UCF101.. I guess one reason could be that most actions in UCF don't require focusing on image regions, as the scene context itself gives away the action..
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Related Issues (20)
- Error: /usr/bin/ld: cannot find -lboost_system HOT 3
- Infer realtime HOT 1
- HICO and HMDB51 dataset HOT 3
- Results of self training + eval are lower than reported HOT 2
- Error while compiling the custom ops HOT 1
- Parameters/HyperParameters for training HICO dataset HOT 2
- File not found: ../experiments/002_MPII_ResNet_withAttention_train+val.yaml HOT 1
- Some implementation queries on dropout, vgg16 last feature map tapping HOT 1
- Training issue about another dataset
- How to install the IlmImf and extra_component library HOT 1
- undefined symbol: _ZN5boost13thread_detail20rollback_once_regionERNS_9once_flagE HOT 3
- Cannot find libs folder for tensorflow_compact_bilinear_pooling HOT 2
- ValueError: need at least one array to concatenate HOT 1
- Hello, can you write an Attentional Pooling version that caffe can use? HOT 1
- Error when running any one of the python files HOT 1
- Failed to find any matching file for resnet_v1_101.ckpt HOT 3
- undefined symbol: _ZTIN10tensorflow8OpKernelE HOT 4
- Classification Output Issue
- attentional pooling layer HOT 1
- About the a_k, b, x_a, x_b in the paper
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