1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
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Abstract (arXiv)
In this technical report, we present our solutions of Waymo Open Dataset (WOD) Challenge 2020 - 2D Object Track. We adopt FPN as our basic framework. Cascade RCNN, stacked PAFPN Neck and Double-Head are used for performance improvements. In order to handle the small object detection problem in WOD, we use very large image scales for both training and testing. Using our methods, our team RW-TSDet achieved the 1st place in the 2D Object Detection Track.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Aug 2020.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 0; 2024: 1.
5 papers.
- 2021Multimodal Object Detection via Probabilistic Ensemblingcited by 67
- 2022Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detectioncited by 35
- 2021USB: Universal-Scale Object Detection Benchmarkcited by 9
- 2021Scale Normalized Image Pyramids with AutoFocus for Object Detectioncited by 5
- 2024A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Trackcited by 0
- 2024A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track27 Feb 2024
- 2022Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection25 Apr 2022
- 2021Multimodal Object Detection via Probabilistic Ensembling7 Apr 2021
- 2021USB: Universal-Scale Object Detection Benchmark25 Mar 2021
- 2021Scale Normalized Image Pyramids with AutoFocus for Object Detection10 Feb 2021