114 citations · 195 across the 8 of their papers we have counts for
8 papers
Aggregation of Disentanglement: Reconsidering Domain Variations in Domain Generalization
Daoan Zhang, Mingkai Chen, Chenming Li +2
Domain Generalization (DG) is a fundamental challenge for machine learning models, which aims to improve model generalization on various domains. Previous methods focus on generati…
A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images
Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit +7
Quantifying the perceptual similarity of two images is a long-standing problem in low-level computer vision. The natural image domain commonly relies on supervised learning, e.g.,…
Rethinking Alignment and Uniformity in Unsupervised Semantic Segmentation
Daoan Zhang, Chenming Li, Haoquan Li +3
Unsupervised image semantic segmentation(UISS) aims to match low-level visual features with semantic-level representations without outer supervision. In this paper, we address the…
Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning
Jiahao Xia, Weiwei qu, Wenjian Huang +3
Heatmap regression methods have dominated face alignment area in recent years while they ignore the inherent relation between different landmarks. In this paper, we propose a Spars…
Detect Faces Efficiently: A Survey and Evaluations
Yuantao Feng, Shiqi Yu, Hanyang Peng +2
Face detection is to search all the possible regions for faces in images and locate the faces if there are any. Many applications including face recognition, facial expression reco…
Mixed Supervised Object Detection with Robust Objectness Transfer
Yan Li, Junge Zhang, Kaiqi Huang +1
In this paper, we consider the problem of leveraging existing fully labeled categories to improve the weakly supervised detection (WSD) of new object categories, which we refer to…
Beyond triplet loss: a deep quadruplet network for person re-identification
Weihua Chen, Xiaotang Chen, Jianguo Zhang +1
Person re-identification (ReID) is an important task in wide area video surveillance which focuses on identifying people across different cameras. Recently, deep learning networks…
A Multi-task Deep Network for Person Re-identification
Weihua Chen, Xiaotang Chen, Jianguo Zhang +1
Person re-identification (ReID) focuses on identifying people across different scenes in video surveillance, which is usually formulated as a binary classification task or a rankin…