251 citations · 2.2k across the 123 of their papers we have counts for
26 papers · 1 filter
Synthetic Training for Monocular Human Mesh Recovery
Yu Sun, Qian Bao, Wu Liu +4
Recovering 3D human mesh from monocular images is a popular topic in computer vision and has a wide range of applications. This paper aims to estimate 3D mesh of multiple body part…
Joint Contrastive Learning with Infinite Possibilities
Qi Cai, Yu Wang, Yingwei Pan +2
This paper explores useful modifications of the recent development in contrastive learning via novel probabilistic modeling. We derive a particular form of contrastive loss named J…
The Elements of End-to-end Deep Face Recognition: A Survey of Recent Advances
Hang Du, Hailin Shi, Dan Zeng +2
Face recognition is one of the most popular and long-standing topics in computer vision. With the recent development of deep learning techniques and large-scale datasets, deep face…
Learning to Localize Actions from Moments
Fuchen Long, Ting Yao, Zhaofan Qiu +3
With the knowledge of action moments (i.e., trimmed video clips that each contains an action instance), humans could routinely localize an action temporally in an untrimmed video.…
Black Re-ID: A Head-shoulder Descriptor for the Challenging Problem of Person Re-Identification
Boqiang Xu, Lingxiao He, Xingyu Liao +3
Person re-identification (Re-ID) aims at retrieving an input person image from a set of images captured by multiple cameras. Although recent Re-ID methods have made great success,…
Monocular, One-stage, Regression of Multiple 3D People
Yu Sun, Qian Bao, Wu Liu +3
This paper focuses on the regression of multiple 3D people from a single RGB image. Existing approaches predominantly follow a multi-stage pipeline that first detects people in bou…
SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning
Ting Yao, Yiheng Zhang, Zhaofan Qiu +2
A steady momentum of innovations and breakthroughs has convincingly pushed the limits of unsupervised image representation learning. Compared to static 2D images, video has one mor…
Pre-training for Video Captioning Challenge 2020 Summary
Yingwei Pan, Jun Xu, Yehao Li +2
The Pre-training for Video Captioning Challenge 2020 Summary: results and challenge participants' technical reports.
Edge-aware Graph Representation Learning and Reasoning for Face Parsing
Gusi Te, Yinglu Liu, Wei Hu +2
Face parsing infers a pixel-wise label to each facial component, which has drawn much attention recently. Previous methods have shown their efficiency in face parsing, which howeve…
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
Haoran Wang, Tong Shen, Wei Zhang +2
Despite great progress in supervised semantic segmentation,a large performance drop is usually observed when deploying the model in the wild. Domain adaptation methods tackle the i…
Semi-Siamese Training for Shallow Face Learning
Hang Du, Hailin Shi, Yuchi Liu +4
Most existing public face datasets, such as MS-Celeb-1M and VGGFace2, provide abundant information in both breadth (large number of IDs) and depth (sufficient number of samples) fo…
FastReID: A Pytorch Toolbox for General Instance Re-identification
Lingxiao He, Xingyu Liao, Wu Liu +3
General Instance Re-identification is a very important task in the computer vision, which can be widely used in many practical applications, such as person/vehicle re-identificatio…
Loss Function Search for Face Recognition
Xiaobo Wang, Shuo Wang, Cheng Chi +2
In face recognition, designing margin-based (e.g., angular, additive, additive angular margins) softmax loss functions plays an important role in learning discriminative features.…
Single Shot Video Object Detector
Jiajun Deng, Yingwei Pan, Ting Yao +3
Single shot detectors that are potentially faster and simpler than two-stage detectors tend to be more applicable to object detection in videos. Nevertheless, the extension of such…
Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training
Yingwei Pan, Yehao Li, Jianjie Luo +3
In this work, we present Auto-captions on GIF, which is a new large-scale pre-training dataset for generic video understanding. All video-sentence pairs are created by automaticall…
NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition
Dan Zeng, Hailin Shi, Hang Du +3
The training scheme of deep face recognition has greatly evolved in the past years, yet it encounters new challenges in the large-scale data situation where massive and diverse har…
Learning a Unified Sample Weighting Network for Object Detection
Qi Cai, Yingwei Pan, Yu Wang +3
Region sampling or weighting is significantly important to the success of modern region-based object detectors. Unlike some previous works, which only focus on "hard" samples when…
Transferring and Regularizing Prediction for Semantic Segmentation
Yiheng Zhang, Zhaofan Qiu, Ting Yao +3
Semantic segmentation often requires a large set of images with pixel-level annotations. In the view of extremely expensive expert labeling, recent research has shown that the mode…
Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation
Yingwei Pan, Ting Yao, Yehao Li +2
Unsupervised domain adaptation has received significant attention in recent years. Most of existing works tackle the closed-set scenario, assuming that the source and target domain…
Learning the Compositional Visual Coherence for Complementary Recommendations
Zhi Li, Bo Wu, Qi Liu +3
Complementary recommendations, which aim at providing users product suggestions that are supplementary and compatible with their obtained items, have become a hot topic in both aca…
Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks
Ning Zhang, Jingen Liu, Ke Wang +2
The current deep learning based visual tracking approaches have been very successful by learning the target classification and/or estimation model from a large amount of supervised…
VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification
Zhedong Zheng, Tao Ruan, Yunchao Wei +2
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and discriminative visual representation, given the significant intra-class vehicle variations acr…
Look-into-Object: Self-supervised Structure Modeling for Object Recognition
Mohan Zhou, Yalong Bai, Wei Zhang +2
Most object recognition approaches predominantly focus on learning discriminative visual patterns while overlooking the holistic object structure. Though important, structure model…
X-Linear Attention Networks for Image Captioning
Yingwei Pan, Ting Yao, Yehao Li +1
Recent progress on fine-grained visual recognition and visual question answering has featured Bilinear Pooling, which effectively models the 2 order interactions across mult…