activity
20172022
most citedINTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

354 citations · 843 across the 69 of their papers we have counts for

collaborators
Showing cs.CVShow all

23 papers · 1 filter

cs.CV202271 cited

Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection

Jinhyung Park, Chenfeng Xu, Shijia Yang +4

While recent camera-only 3D detection methods leverage multiple timesteps, the limited history they use significantly hampers the extent to which temporal fusion can improve object…

cs.CV2022

PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map

Chenfeng Xu, Tian Li, Chen Tang +5

Deep learning has recently achieved significant progress in trajectory forecasting. However, the scarcity of trajectory data inhibits the data-hungry deep-learning models from lear…

cs.CV20223 cited

DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object Detection

Jinhyung Park, Chenfeng Xu, Yiyang Zhou +2

While numerous 3D detection works leverage the complementary relationship between RGB images and point clouds, developments in the broader framework of semi-supervised object recog…

cs.CV2022

Important Object Identification with Semi-Supervised Learning for Autonomous Driving

Jiachen Li, Haiming Gang, Hengbo Ma +2

Accurate identification of important objects in the scene is a prerequisite for safe and high-quality decision making and motion planning of intelligent agents (e.g., autonomous ve…

cs.CV20211 cited

RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting

Jiachen Li, Fan Yang, Hengbo Ma +3

Motion forecasting plays a significant role in various domains (e.g., autonomous driving, human-robot interaction), which aims to predict future motion sequences given a set of his…

cs.CV20214 cited

Spectral Temporal Graph Neural Network for Trajectory Prediction

Defu Cao, Jiachen Li, Hengbo Ma +1

An effective understanding of the contextual environment and accurate motion forecasting of surrounding agents is crucial for the development of autonomous vehicles and social mobi…