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EdenGabriel avatar EdenGabriel commented on June 12, 2024

oh, I discovered that when I tried using VGG (obtained from UMT) features, the model also failed to learn effectively. It only worked when using SlowFast + Clip features.

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EdenGabriel avatar EdenGabriel commented on June 12, 2024

the configuration as follows:

dset_name=charades
ctx_mode=video_tef
v_feat_types=c3d
t_feat_type=clip 
results_root=results
exp_id=exp

if [[ ${v_feat_types} == *"c3d"* ]]; then
  v_feat_dirs+=(${feat_root}/charades_c3d_raw)
  (( v_feat_dim += 1024 ))
fi
if [[ ${v_feat_types} == *"rgb"* ]]; then
  v_feat_dirs+=(${feat_root}/charades_rgb_opt/rgb_features)
  (( v_feat_dim += 4096 ))
fi

bsz=32
n_epoch=100
lr_drop=40
lr=0.0002
lw_saliency=4.0
max_v_l=-1
max_q_l=32
clip_length=1


PYTHONPATH=$PYTHONPATH:. python qd_detr/train.py \
--dset_name ${dset_name} \
--ctx_mode ${ctx_mode} \
--train_path ${train_path} \
--eval_path ${eval_path} \
--eval_split_name ${eval_split_name} \
--v_feat_dirs ${v_feat_dirs[@]} \
--v_feat_dim ${v_feat_dim} \
--t_feat_dir ${t_feat_dir} \
--t_feat_dim ${t_feat_dim} \
--bsz ${bsz} \
--n_epoch ${n_epoch} \
--lr_drop ${lr_drop} \
--lr ${lr} \
--lw_saliency ${lw_saliency} \
--max_v_l ${max_v_l} \
--max_q_l ${max_q_l} \
--clip_length ${clip_length} \
--results_root ${results_root}_charades \
--exp_id ${exp_id} \
${@:1}

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EdenGabriel avatar EdenGabriel commented on June 12, 2024

Sorry for bothering you. I have resolved the issue. I overlooked the fact that different features corresponded to different clip lengths.

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wjun0830 avatar wjun0830 commented on June 12, 2024

Great! Thanks.

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wjun0830 avatar wjun0830 commented on June 12, 2024

We are very sorry for the inconvenience.
Charades-STA experiments with C3D features are actually conducted with I3D features and I3D benchmarking tables.
Features are provided here from VSLNET.

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