activity
20182021
most citedInstance-Aware Predictive Navigation in Multi-Agent Environments

1 citations · 1 across the 1 of their papers we have counts for

collaborators

6 papers

cs.CV20229 cited

Track Targets by Dense Spatio-Temporal Position Encoding

Jinkun Cao, Hao Wu, Kris Kitani

In this work, we propose a novel paradigm to encode the position of targets for target tracking in videos using transformers. The proposed paradigm, Dense Spatio-Temporal (DST) pos…

cs.RO20211 cited

Instance-Aware Predictive Navigation in Multi-Agent Environments

Jinkun Cao, Xin Wang, Trevor Darrell +1

In this work, we aim to achieve efficient end-to-end learning of driving policies in dynamic multi-agent environments. Predicting and anticipating future events at the object level…

cs.CV2020

TransTrack: Multiple Object Tracking with Transformer

Peize Sun, Jinkun Cao, Yi Jiang +5

In this work, we propose TransTrack, a simple but efficient scheme to solve the multiple object tracking problems. TransTrack leverages the transformer architecture, which is an at…

cs.CV2019

Attribute Restoration Framework for Anomaly Detection

Chaoqin Huang, Fei Ye, Jinkun Cao +3

With the recent advances in deep neural networks, anomaly detection in multimedia has received much attention in the computer vision community. While reconstruction-based methods h…

cs.CV2019

Cross-Domain Adaptation for Animal Pose Estimation

Jinkun Cao, Hongyang Tang, Hao-Shu Fang +3

In this paper, we are interested in pose estimation of animals. Animals usually exhibit a wide range of variations on poses and there is no available animal pose dataset for traini…

cs.CV2018

Pairwise Body-Part Attention for Recognizing Human-Object Interactions

Hao-Shu Fang, Jinkun Cao, Yu-Wing Tai +1

In human-object interactions (HOI) recognition, conventional methods consider the human body as a whole and pay a uniform attention to the entire body region. They ignore the fact…