most citedQuality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking

5 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20231 cited

ChatSpot: Bootstrapping Multimodal LLMs via Precise Referring Instruction Tuning

Liang Zhao, En Yu, Zheng Ge +8

Human-AI interactivity is a critical aspect that reflects the usability of multimodal large language models (MLLMs). However, existing end-to-end MLLMs only allow users to interact…

cs.CV20231 cited

GroupLane: End-to-End 3D Lane Detection with Channel-wise Grouping

Zhuoling Li, Chunrui Han, Zheng Ge +5

Efficiency is quite important for 3D lane detection due to practical deployment demand. In this work, we propose a simple, fast, and end-to-end detector that still maintains high d…

cs.CV20232 cited

BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo

Yinhao Li, Jinrong Yang, Jianjian Sun +3

Bounded by the inherent ambiguity of depth perception, contemporary multi-view 3D object detection methods fall into the performance bottleneck. Intuitively, leveraging temporal mu…

cs.CV20225 cited

Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking

Jinrong Yang, En Yu, Zeming Li +2

3D Multi-Object Tracking (MOT) has achieved tremendous achievement thanks to the rapid development of 3D object detection and 2D MOT. Recent advanced works generally employ a serie…

cs.CV20222 cited

StreamYOLO: Real-time Object Detection for Streaming Perception

Jinrong Yang, Songtao Liu, Zeming Li +2

The perceptive models of autonomous driving require fast inference within a low latency for safety. While existing works ignore the inevitable environmental changes after processin…