activity
20192026
most citedWhere2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps

70 citations · 84 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2026

FF3R: Feedforward Feature 3D Reconstruction from Unconstrained views

Chaoyi Zhou, Run Wang, Feng Luo +4

Recent advances in vision foundation models have revolutionized geometry reconstruction and semantic understanding. Yet, most of the existing approaches treat these capabilities in…

cs.CV2024

Boosting Generalizability towards Zero-Shot Cross-Dataset Single-Image Indoor Depth by Meta-Initialization

Cho-Ying Wu, Yiqi Zhong, Junying Wang +1

Indoor robots rely on depth to perform tasks like navigation or obstacle detection, and single-image depth estimation is widely used to assist perception. Most indoor single-image…

cs.CV2024

Self-Supervised Bird's Eye View Motion Prediction with Cross-Modality Signals

Shaoheng Fang, Zuhong Liu, Mingyu Wang +3

Learning the dense bird's eye view (BEV) motion flow in a self-supervised manner is an emerging research for robotics and autonomous driving. Current self-supervised methods mainly…

cs.CV20242 cited

An Extensible Framework for Open Heterogeneous Collaborative Perception

Yifan Lu, Yue Hu, Yiqi Zhong +3

Collaborative perception aims to mitigate the limitations of single-agent perception, such as occlusions, by facilitating data exchange among multiple agents. However, most current…

cs.CV20237 cited

Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow

Sizhe Wei, Yuxi Wei, Yue Hu +4

Collaborative perception can substantially boost each agent's perception ability by facilitating communication among multiple agents. However, temporal asynchrony among agents is i…

cs.CV20231 cited

MMVP: Motion-Matrix-based Video Prediction

Yiqi Zhong, Luming Liang, Ilya Zharkov +1

A central challenge of video prediction lies where the system has to reason the objects' future motions from image frames while simultaneously maintaining the consistency of their…