activity
20192022
most citedReal-Time Visual Object Tracking via Few-Shot Learning

3 citations · 6 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20222 cited

Non-Contrastive Learning Meets Language-Image Pre-Training

Jinghao Zhou, Li Dong, Zhe Gan +2

Contrastive language-image pre-training (CLIP) serves as a de-facto standard to align images and texts. Nonetheless, the loose correlation between images and texts of web-crawled d…

cs.CV2021

CAT: Cross-Attention Transformer for One-Shot Object Detection

Weidong Lin, Yuyan Deng, Yang Gao +5

Given a query patch from a novel class, one-shot object detection aims to detect all instances of that class in a target image through the semantic similarity comparison. However,…

cs.CV20211 cited

Instance and Pair-Aware Dynamic Networks for Re-Identification

Bingliang Jiao, Xin Tan, Jinghao Zhou +3

Re-identification (ReID) is to identify the same instance across different cameras. Existing ReID methods mostly utilize alignment-based or attention-based strategies to generate e…

cs.CV20213 cited

Real-Time Visual Object Tracking via Few-Shot Learning

Jinghao Zhou, Bo Li, Peng Wang +5

Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL). While the concept of FSL is not new in tracking and has been previously applied by prior wo…

cs.CV2021

Higher Performance Visual Tracking with Dual-Modal Localization

Jinghao Zhou, Bo Li, Lei Qiao +5

Visual Object Tracking (VOT) has synchronous needs for both robustness and accuracy. While most existing works fail to operate simultaneously on both, we investigate in this work t…

cs.CV2021

Pluggable Weakly-Supervised Cross-View Learning for Accurate Vehicle Re-Identification

Lu Yang, Hongbang Liu, Jinghao Zhou +4

Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under…