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FasterViT: Fast Vision Transformers with Hierarchical Attention

Object Tracking with MOTRv2

Official PyTorch implementation of FasterViT: Fast Vision Transformers with Hierarchical Attention.


In this section, we introduce the FasterViT object tracking repository with MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors.

Main Results

DanceTrack

The FasterViT-4-21K-224 model demonstrated superior performance in both the validation and test datasets, outperforming the MOTRv2 algorithm with ResNet50.

Backbone/Train Recipes Validset Testset Backbone/Train Recipes Validset Testset
ResNet50 65.3 69.9 *FasterViT 67.4 (2.1↑) 71.0 (1.1↑)
ResNet50 + *TrainVal - 70.9 FasterViT + TrainVal (model) - 73.7 (2.8↑)
ResNet50 + TrainVal + 4 Model Ensemble - 72.9 FasterViT + TrainVal + 4 Model Ensemble - WIP
ResNet50 + TrainVal + 4 Model Ensemble + Extra Association - 73.4 FasterViT + TrainVal + 4 Model Ensemble + Extra Association - WIP

* TrainVal: Jointly trained on the training and validation sets.

* FasterViT: Utilized the FasterViT-4-21K-224 model as the backbone.

Installation and Dataset Preparation

The codebase is built on top of Deformable DETR and MOTRv2. We recommend following the installation instructions and dataset preparation.

Usage

Training

To initiate training, start by downloading the pretrained weights for COCO from Deformable DETR (+ iterative bounding box refinement). Then, modify the --pretrained argument with the path to the downloaded weights. Proceed to train MOTR on 8 GPUs using the following command:

./tools/ddp_train.sh downstream/object_tracking/motrv2/configs/motrv2.args downstream/object_tracking/motrv2/results /data/Dataset/mot /data/Dataset/mot/det_db_motrv2.json 8

Inference on DanceTrack Testset

For running inference on the DanceTrack testset with multiple trained weights, execute the following command:

# ./tools/simple_inference_test_parallel.sh <config-file> <weights-dir> <gpu-num> <output-dir> <mot-path-dir> <db-file> 
./tools/simple_inference_test_parallel.sh configs/motrv2.args downstream/object_tracking/motrv2/results 8 submit/ /data/Dataset/mot /data/Dataset/mot/det_db_motrv2.json

Acknowledgements