Causality In Traffic Accident (Under Construction)
Repository for Traffic Accident Benchmark for Causality Recognition (ECCV 2020)
Overview
Data Preparation
Details of dataset construction
Benchmark
Cause and Effect Event Classification
We adopt Temporal Segment Networks (ECCV 2016) from the repository https://github.com/yjxiong/tsn-pytorch
- The default arguments for code are set to train TSN with average consensus function.
python train_classifier.py --consensus_type average
python train_classifier.py --consensus_type linear
Temporal Cause and Effect Event Localization
We adopt three types of baseline methods in our benchmark.
- Single-stage Action Detection
python train_localization.py --architecture_type forward-SST
python train_localization.py --architecture_type backward-SST
python train_localization.py --architecture_type bi-SST
python train_localization.py --architecture_type SSTCN-SST
- Proposal-based Action Detection (Not supported yet)
python train_localization.py --architecture_type naive-conv-R-C3D
python train_localization.py --architecture_type SSTCN-R-C3D
- Action Segmentation
python train_localization.py --architecture_type SSTCN-Segmentation
python train_localization.py --architecture_type MSTCN-Segmentation