most citedHiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention

11 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2023

Refining Obstacle Perception Safety Zones via Maneuver-Based Decomposition

Sever Topan, Yuxiao Chen, Edward Schmerling +4

A critical task for developing safe autonomous driving stacks is to determine whether an obstacle is safety-critical, i.e., poses an imminent threat to the autonomous vehicle. Our…

cs.CV2023

Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens

Yuxiao Chen, Jianbo Yuan, Yu Tian +5

Contrastive learning-based vision-language pre-training approaches, such as CLIP, have demonstrated great success in many vision-language tasks. These methods achieve cross-modal a…

cs.RO20231 cited

Learning Responsibility Allocations for Safe Human-Robot Interaction with Applications to Autonomous Driving

Ryan K. Cosner, Yuxiao Chen, Karen Leung +1

Drivers have a responsibility to exercise reasonable care to avoid collision with other road users. This assumed responsibility allows interacting agents to maintain safety without…

cs.CV202311 cited

HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention

Shijie Geng, Jianbo Yuan, Yu Tian +2

The success of large-scale contrastive vision-language pretraining (CLIP) has benefited both visual recognition and multimodal content understanding. The concise design brings CLIP…

cs.RO2023

Tree-structured Policy Planning with Learned Behavior Models

Yuxiao Chen, Peter Karkus, Boris Ivanovic +2

Autonomous vehicles (AVs) need to reason about the multimodal behavior of neighboring agents while planning their own motion. Many existing trajectory planners seek a single trajec…

cs.RO2022

BITS: Bi-level Imitation for Traffic Simulation

Danfei Xu, Yuxiao Chen, Boris Ivanovic +1

Simulation is the key to scaling up validation and verification for robotic systems such as autonomous vehicles. Despite advances in high-fidelity physics and sensor simulation, a…