57 citations · 164 across the 14 of their papers we have counts for
15 papers
Point2Mask: Point-supervised Panoptic Segmentation via Optimal Transport
Wentong Li, Yuqian Yuan, Song Wang +4
Weakly-supervised image segmentation has recently attracted increasing research attentions, aiming to avoid the expensive pixel-wise labeling. In this paper, we present an effectiv…
Multi-Forgery Detection Challenge 2022: Push the Frontier of Unconstrained and Diverse Forgery Detection
Jianshu Li, Man Luo, Jian Liu +12
In this paper, we present the Multi-Forgery Detection Challenge held concurrently with the IEEE Computer Society Workshop on Biometrics at CVPR 2022. Our Multi-Forgery Detection Ch…
A Unified Framework for Biphasic Facial Age Translation with Noisy-Semantic Guided Generative Adversarial Networks
Muyi Sun, Jian Wang, Yunfan Liu +2
Biphasic facial age translation aims at predicting the appearance of the input face at any age. Facial age translation has received considerable research attention in the last deca…
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
Yuanhan Zhang, Zhenfei Yin, Jing Shao +22
As facial interaction systems are prevalently deployed, security and reliability of these systems become a critical issue, with substantial research efforts devoted. Among them, fa…
Multi-Prototype Networks for Unconstrained Set-based Face Recognition
Jian Zhao, Jianshu Li, Xiaoguang Tu +6
In this paper, we study the challenging unconstrained set-based face recognition problem where each subject face is instantiated by a set of media (images and videos) instead of a…
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing
Xiaoguang Tu, Jian Zhao, Mei Xie +5
Face anti-spoofing (a.k.a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems. Existing CNN-based approaches u…
-Nets: Double Attention Networks
Yunpeng Chen, Yannis Kalantidis, Jianshu Li +2
Learning to capture long-range relations is fundamental to image/video recognition. Existing CNN models generally rely on increasing depth to model such relations which is highly i…
Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
Jian Zhao, Yu Cheng, Yi Cheng +12
Despite the remarkable progress in face recognition related technologies, reliably recognizing faces across ages still remains a big challenge. The appearance of a human face chang…
Object Relation Detection Based on One-shot Learning
Li Zhou, Jian Zhao, Jianshu Li +2
Detecting the relations among objects, such as "cat on sofa" and "person ride horse", is a crucial task in image understanding, and beneficial to bridging the semantic gap between…
Multi-Fiber Networks for Video Recognition
Yunpeng Chen, Yannis Kalantidis, Jianshu Li +2
In this paper, we aim to reduce the computational cost of spatio-temporal deep neural networks, making them run as fast as their 2D counterparts while preserving state-of-the-art a…
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing
Jian Zhao, Jianshu Li, Yu Cheng +4
Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding huma…
Weaving Multi-scale Context for Single Shot Detector
Yunpeng Chen, Jianshu Li, Bin Zhou +2
Aggregating context information from multiple scales has been proved to be effective for improving accuracy of Single Shot Detectors (SSDs) on object detection. However, existing m…
Integrated Face Analytics Networks through Cross-Dataset Hybrid Training
Jianshu Li, Shengtao Xiao, Fang Zhao +5
Face analytics benefits many multimedia applications. It consists of a number of tasks, such as facial emotion recognition and face parsing, and most existing approaches generally…
Multiple-Human Parsing in the Wild
Jianshu Li, Jian Zhao, Yunchao Wei +5
Human parsing is attracting increasing research attention. In this work, we aim to push the frontier of human parsing by introducing the problem of multi-human parsing in the wild.…
Multi-stage Object Detection with Group Recursive Learning
Jianan Li, Xiaodan Liang, Jianshu Li +3
Most of existing detection pipelines treat object proposals independently and predict bounding box locations and classification scores over them separately. However, the important…