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Runzhou Ge

4 accepted papers

2024

MoST: Multi-Modality Scene Tokenization for Motion Prediction

CVPR 2024poster

Many existing motion prediction approaches rely on symbolic perception outputs to generate agent trajectories such as bounding boxes road graph information and traffic lights. This symbolic representation is a high-level abstraction of the real world which may render the motion prediction model vuln…

Cited by 9SourcePDFScholar
2024

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting

ICRA 2024poster

Widely adopted motion forecasting datasets sub-stitute the observed sensory inputs with higher-level abstractions such as 3D boxes and polylines. These sparse shapes are inferred through annotating the original scenes with perception systems’ predictions. Such intermediate representations tie the qu…

Cited by 28SourceScholar
2022

AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Clouds

AAAI 2022technical

There have been two streams in the 3D detection from point clouds: single-stage methods and two-stage methods. While the former is more computationally efficient, the latter usually provides better detection accuracy. By carefully examining the two-stage approaches, we have found that if appropriate…

2018

Motion-Appearance Co-Memory Networks for Video Question Answering

CVPR 2018poster

Video Question Answering (QA) is an important task in understanding video temporal structure. We observe that there are three unique attributes of video QA compared with image QA: (1) it deals with long sequences of images containing richer information not only in quantity but also in variety; (2) m…

Cited by 310SourcePDFScholar