105 citations · 277 across the 34 of their papers we have counts for
24 papers · 1 filter
Global-correlated 3D-decoupling Transformer for Clothed Avatar Reconstruction
Zechuan Zhang, Li Sun, Zongxin Yang +2
Reconstructing 3D clothed human avatars from single images is a challenging task, especially when encountering complex poses and loose clothing. Current methods exhibit limitations…
LOGICSEG: Parsing Visual Semantics with Neural Logic Learning and Reasoning
Liulei Li, Wenguan Wang, Yi Yang
Current high-performance semantic segmentation models are purely data-driven sub-symbolic approaches and blind to the structured nature of the visual world. This is in stark contra…
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation
Yuanyou Xu, Zongxin Yang, Yi Yang
Tracking any given object(s) spatially and temporally is a common purpose in Visual Object Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation have…
JOTR: 3D Joint Contrastive Learning with Transformers for Occluded Human Mesh Recovery
Jiahao Li, Zongxin Yang, Xiaohan Wang +3
In this study, we focus on the problem of 3D human mesh recovery from a single image under obscured conditions. Most state-of-the-art methods aim to improve 2D alignment technologi…
TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering
Xiao Pan, Zongxin Yang, Jianxin Ma +2
In this paper, we focus on the task of generalizable neural human rendering which trains conditional Neural Radiance Fields (NeRF) from multi-view videos of different characters. T…
AvatarFusion: Zero-shot Generation of Clothing-Decoupled 3D Avatars Using 2D Diffusion
Shuo Huang, Zongxin Yang, Liangting Li +2
Large-scale pre-trained vision-language models allow for the zero-shot text-based generation of 3D avatars. The previous state-of-the-art method utilized CLIP to supervise neural i…
Collaborative Group: Composed Image Retrieval via Consensus Learning from Noisy Annotations
Xu Zhang, Zhedong Zheng, Linchao Zhu +1
Composed image retrieval extends content-based image retrieval systems by enabling users to search using reference images and captions that describe their intention. Despite great…
Counterfactual Co-occurring Learning for Bias Mitigation in Weakly-supervised Object Localization
Feifei Shao, Yawei Luo, Lei Chen +4
Contemporary weakly-supervised object localization (WSOL) methods have primarily focused on addressing the challenge of localizing the most discriminative region while largely over…
Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models
Wenhao Wu, Xiaohan Wang, Haipeng Luo +3
Vision-language models (VLMs) pre-trained on large-scale image-text pairs have demonstrated impressive transferability on various visual tasks. Transferring knowledge from such pow…
StepNet: Spatial-temporal Part-aware Network for Isolated Sign Language Recognition
Xiaolong Shen, Zhedong Zheng, Yi Yang
The goal of sign language recognition (SLR) is to help those who are hard of hearing or deaf overcome the communication barrier. Most existing approaches can be typically divided i…
PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation
Mu Chen, Zhedong Zheng, Yi Yang +1
Unsupervised Domain Adaptation (UDA) aims to enhance the generalization of the learned model to other domains. The domain-invariant knowledge is transferred from the model trained…
Learning Cross-view Geo-localization Embeddings via Dynamic Weighted Decorrelation Regularization
Tingyu Wang, Zhedong Zheng, Zunjie Zhu +3
Cross-view geo-localization aims to spot images of the same location shot from two platforms, e.g., the drone platform and the satellite platform. Existing methods usually focus on…
Feature-Proxy Transformer for Few-Shot Segmentation
Jian-Wei Zhang, Yifan Sun, Yi Yang +1
Few-shot segmentation (FSS) aims at performing semantic segmentation on novel classes given a few annotated support samples. With a rethink of recent advances, we find that the cur…
GPPF: A General Perception Pre-training Framework via Sparsely Activated Multi-Task Learning
Benyuan Sun, Jin Dai, Zihao Liang +3
Pre-training over mixtured multi-task, multi-domain, and multi-modal data remains an open challenge in vision perception pre-training. In this paper, we propose GPPF, a General Per…
Jointly Harnessing Prior Structures and Temporal Consistency for Sign Language Video Generation
Yucheng Suo, Zhedong Zheng, Xiaohan Wang +2
Sign language is the window for people differently-abled to express their feelings as well as emotions. However, it remains challenging for people to learn sign language in a short…
3D Magic Mirror: Clothing Reconstruction from a Single Image via a Causal Perspective
Zhedong Zheng, Jiayin Zhu, Wei Ji +2
This research aims to study a self-supervised 3D clothing reconstruction method, which recovers the geometry shape and texture of human clothing from a single image. Compared with…
Multiple-environment Self-adaptive Network for Aerial-view Geo-localization
Tingyu Wang, Zhedong Zheng, Yaoqi Sun +3
Aerial-view geo-localization tends to determine an unknown position through matching the drone-view image with the geo-tagged satellite-view image. This task is mostly regarded as…
Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic Segmentation
Yulei Lu, Yawei Luo, Li Zhang +3
A thriving trend for domain adaptive segmentation endeavors to generate the high-quality pseudo labels for target domain and retrain the segmentor on them. Under this self-training…
Deep Hierarchical Semantic Segmentation
Liulei Li, Tianfei Zhou, Wenguan Wang +2
Humans are able to recognize structured relations in observation, allowing us to decompose complex scenes into simpler parts and abstract the visual world in multiple levels. Howev…
Automated Progressive Learning for Efficient Training of Vision Transformers
Changlin Li, Bohan Zhuang, Guangrun Wang +3
Recent advances in vision Transformers (ViTs) have come with a voracious appetite for computing power, high-lighting the urgent need to develop efficient training methods for ViTs.…
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate Domains
Yongxing Dai, Yifan Sun, Jun Liu +3
Cross-domain person re-identification (re-ID), such as unsupervised domain adaptive (UDA) re-ID, aims to transfer the identity-discriminative knowledge from the source to the targe…
Local-Global Context Aware Transformer for Language-Guided Video Segmentation
Chen Liang, Wenguan Wang, Tianfei Zhou +3
We explore the task of language-guided video segmentation (LVS). Previous algorithms mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context and…
Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes
Chao Sun, Zhedong Zheng, Xiaohan Wang +2
The manual annotation for large-scale point clouds costs a lot of time and is usually unavailable in harsh real-world scenarios. Inspired by the great success of the pre-training a…
LID 2020: The Learning from Imperfect Data Challenge Results
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…