212 citations · 247 across the 9 of their papers we have counts for
9 papers
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…
Exploring Target Representations for Masked Autoencoders
Xingbin Liu, Jinghao Zhou, Tao Kong +2
Masked autoencoders have become popular training paradigms for self-supervised visual representation learning. These models randomly mask a portion of the input and reconstruct the…
iBOT: Image BERT Pre-Training with Online Tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang +4
The success of language Transformers is primarily attributed to the pretext task of masked language modeling (MLM), where texts are first tokenized into semantically meaningful pie…
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,…
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…
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…
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…
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…
Discriminative and Robust Online Learning for Siamese Visual Tracking
Jinghao Zhou, Peng Wang, Haoyang Sun
The problem of visual object tracking has traditionally been handled by variant tracking paradigms, either learning a model of the object's appearance exclusively online or matchin…