2 citations · 5 across the 4 of their papers we have counts for
5 papers
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation
En Yu, Songtao Liu, Zhuoling Li +4
Although existing multi-object tracking (MOT) algorithms have obtained competitive performance on various benchmarks, almost all of them train and validate models on the same domai…
Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection
Zhuoling Li, Zhan Qu, Yang Zhou +3
As an inherently ill-posed problem, depth estimation from single images is the most challenging part of monocular 3D object detection (M3OD). Many existing methods rely on preconce…
Towards Discriminative Representation: Multi-view Trajectory Contrastive Learning for Online Multi-object Tracking
En Yu, Zhuoling Li, Shoudong Han
Discriminative representation is crucial for the association step in multi-object tracking. Recent work mainly utilizes features in single or neighboring frames for constructing me…
RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation
En Yu, Zhuoling Li, Shoudong Han +1
Existing online multiple object tracking (MOT) algorithms often consist of two subtasks, detection and re-identification (ReID). In order to enhance the inference speed and reduce…
Enabling the Network to Surf the Internet
Zhuoling Li, Haohan Wang, Tymoteusz Swistek +3
Few-shot learning is challenging due to the limited data and labels. Existing algorithms usually resolve this problem by pre-training the model with a considerable amount of annota…