code release

README.md

@@ -1,6 +1,6 @@
 # Comp4D: LLM-Guided Compositional 4D Scene Generation
 
-The official implementation of "Comp4D: LLM-Guided Compositional 4D Scene Generation".
+The official implementation of paper "Comp4D: LLM-Guided Compositional 4D Scene Generation".
 
 [[Project Page]](https://vita-group.github.io/Comp4D/) | [[Video (narrated)]](https://www.youtube.com/watch?v=9q8SV1Xf_Xw) | [[Video (results)]](https://www.youtube.com/watch?v=gXVoPTGb734) | [[Paper]](https://github.com/VITA-Group/Comp4D/blob/main/assets/Comp4D.pdf) | [[Arxiv]](https://arxiv.org/abs/2403.16993)
 
@@ -48,15 +48,15 @@ pip install ./simple-knn
 
 #### Compositional Scene training
 ```
-python train_comp.py --configs arguments/comp_butterfly_flower_zs.py -e butterflyflower_exp --cfg_override 100.0 --image_weight_override 0.02 --nn_weight 1000 --with_reg  --loss_dx_weight_override 0.005
+python train_comp.py --configs arguments/comp_butterfly_flower_zs.py --expname butterflyflower_exp --cfg_override 100.0 --image_weight_override 0.02 --nn_weight 1000 --with_reg  --loss_dx_weight_override 0.005
 ```
 --- 
 We provide a quick overview of some important arguments:  
+- `--expname`:  Experimental path.
 - `--configs`: Configuration of scene traning including prompt, object identity, object scales, trajectory.
 - `--image_weight`: Weight of sds loss from image-based diffusion model.
 - `--nn_weight`: Weight of k-nn based rigidity loss.
 - `--loss_dx_weight`: Weight of regularization acceleration loss.
-- `-e`:  Experimental path.
 You can also use [VideoCrafter](https://github.com/AILab-CVC/VideoCrafter) in replace of Zeroscope for video-based diffusion model.
 
 #### Rendering

train_comp.sh

@@ -1,4 +1,4 @@
-# python train_comp.py --configs arguments/comp_butterfly_flower_zs.py -e butterflyflower_zs --image_weight_override 0.02 --nn_weight 1000 --with_reg --cfg_override 100.0 --loss_dx_weight_override 0.005
-# python train_comp.py --configs arguments/comp_butterfly_flower_vc.py -e butterflyflower_vc --image_weight_override 0.05 --nn_weight 1000 --with_reg --cfg_override 20.0 --loss_dx_weight_override 0.005 
-# python train_comp.py --configs arguments/comp_fish_rock_zs.py -e fishrock_zs --image_weight_override 0.02 --nn_weight 1000 --with_reg --cfg_override 100.0 --loss_dx_weight_override 0.01
-# python train_comp.py --configs arguments/comp_fish_rock_vc.py -e fishrock_vc --image_weight_override 0.05 --nn_weight 1000 --with_reg --cfg_override 20.0 --loss_dx_weight_override 0.01
+# python train_comp.py --configs arguments/comp_butterfly_flower_zs.py --expname butterflyflower_zs --image_weight_override 0.02 --nn_weight 1000 --with_reg --cfg_override 100.0 --loss_dx_weight_override 0.005
+# python train_comp.py --configs arguments/comp_butterfly_flower_vc.py --expname butterflyflower_vc --image_weight_override 0.05 --nn_weight 1000 --with_reg --cfg_override 20.0 --loss_dx_weight_override 0.005 
+# python train_comp.py --configs arguments/comp_fish_rock_zs.py --expname fishrock_zs --image_weight_override 0.02 --nn_weight 1000 --with_reg --cfg_override 100.0 --loss_dx_weight_override 0.01
+# python train_comp.py --configs arguments/comp_fish_rock_vc.py --expname fishrock_vc --image_weight_override 0.05 --nn_weight 1000 --with_reg --cfg_override 20.0 --loss_dx_weight_override 0.01