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Dataset Preparation

Training data

or you can download and organize the original data from VTG-IT, TimeIT, TimePro, HTStep and LongVid.

Testing data

folder structure:

dataset                                                                           
β”œβ”€ timer1          
β”‚  β”œβ”€ annotations          
β”‚  β”‚  β”œβ”€ train_2k5.json                                                              
β”‚  β”‚  └─ tvgbench.json    
β”‚  β”œβ”€ videos                                                                      
β”‚  β”‚  β”œβ”€ timerft_data                                                                 
β”‚  β”‚  |  β”œβ”€ xxx.mp4       
β”‚  β”‚  β”‚  └─ ...
β”‚  β”‚  β”œβ”€ tvgbench_data                                                                      
β”‚  β”‚  |  β”œβ”€ xxx.mp4      
β”‚  β”‚  β”‚  └─ ...
β”œβ”€ activitynet                                                                    
β”‚  β”œβ”€ annotations                                                                 
β”‚  β”‚  β”œβ”€ sentence_temporal_grounding                                              
β”‚  β”‚  β”‚  └─ test.json                                                             
β”‚  β”œβ”€ videos                                                                      
β”‚  |  β”œβ”€ v_zzz_3yWpTXo.mp4       
β”‚  β”‚  └─ ...
β”œβ”€ charades                                                                       
β”‚  β”œβ”€ Charades_anno                                                               
β”‚  β”‚  └─ Charades_v1_test.csv                                                     
β”‚  β”œβ”€ Charades_v1                                                                 
β”‚  |  β”œβ”€ 0I0FX.mp4    
β”‚  β”‚  └─ ...
β”œβ”€ mvbench                                       
β”‚  β”œβ”€ json                                          
β”‚  β”‚  β”œβ”€ action_antonym.json                        
β”‚  β”‚  └─ ...               
β”‚  β”œβ”€ videos                                       
β”‚  β”‚  β”œβ”€ clevrer
β”‚  β”‚  └─ ...
β”œβ”€ tempcompass                                       
β”‚  β”œβ”€ questions                                      
β”‚  β”‚  β”œβ”€ multi-choice.json                        
β”‚  β”‚  └─ ...               
β”‚  β”œβ”€ videos                                       
β”‚  β”‚  β”œβ”€ 315784.mp4
β”‚  β”‚  └─ ...
β”œβ”€ egoschema                                       
β”‚  β”œβ”€ MC                                           
β”‚  β”‚  └─ test-00000-of-00001.parquet               
β”‚  β”œβ”€ Subset                                       
β”‚  β”‚  └─ test-00000-of-00001.parquet               
β”‚  β”œβ”€ videos                                       
β”‚  β”‚  β”œβ”€ 001934bb-81bd-4cd8-a574-0472ef3f6678.mp4  
β”‚  β”‚  └─ ...
β”œβ”€ videomme                                       
β”‚  β”œβ”€ videomme                                           
β”‚  β”‚  └─ test-00000-of-00001.parquet               
β”‚  β”œβ”€ data                                       
β”‚  β”‚  β”œβ”€ _8lBR0E_Tx8.mp4     
└─ └─ └─ ...                                                          

ActivityNet

Download link: ActivityNet

For fine-tuning setting, before training, you need to preprocess the video data.

bash preprocess_video.sh

Specify the path to the Charades-STA dataset (video files, annotations, etc.).

Charades

Download link: Charades-v1

For fine-tuning setting, before training, you need to preprocess the video data.

bash preprocess_video.sh

Specify the path to the Charades-STA dataset (video files, annotations, etc.).

TVGBench

Download link: hf: Boshenxx/TimeR1-Dataset

MVBench

We place the annotation file of tvgbench in dataset/trainval/tvgbench.json.

Download link: hf: OpenGVLab/MVBench

VideoMME

Download link: hf: lmms-lab/MVBench

Egoschema

Download link: hf: lmms-lab/egoschema

TempCompass

Download link: hf: lmms-lab/TempCompass