416 citations · 2.7k across the 106 of their papers we have counts for
12 papers · 1 filter
Improved Distribution Matching for Dataset Condensation
Ganlong Zhao, Guanbin Li, Yipeng Qin +1
Dataset Condensation aims to condense a large dataset into a smaller one while maintaining its ability to train a well-performing model, thus reducing the storage cost and training…
SketchMetaFace: A Learning-based Sketching Interface for High-fidelity 3D Character Face Modeling
Zhongjin Luo, Dong Du, Heming Zhu +3
Modeling 3D avatars benefits various application scenarios such as AR/VR, gaming, and filming. Character faces contribute significant diversity and vividity as a vital component of…
Exploration and Exploitation of Unlabeled Data for Open-Set Semi-Supervised Learning
Ganlong Zhao, Guanbin Li, Yipeng Qin +5
In this paper, we address a complex but practical scenario in semi-supervised learning (SSL) named open-set SSL, where unlabeled data contain both in-distribution (ID) and out-of-d…
EGC: Image Generation and Classification via a Diffusion Energy-Based Model
Qiushan Guo, Chuofan Ma, Yi Jiang +3
Learning image classification and image generation using the same set of network parameters is a challenging problem. Recent advanced approaches perform well in one task often exhi…
Multi-Level Contrastive Learning for Dense Prediction Task
Qiushan Guo, Yizhou Yu, Yi Jiang +3
In this work, we present Multi-Level Contrastive Learning for Dense Prediction Task (MCL), an efficient self-supervised method for learning region-level feature representation for…
Protein Representation Learning via Knowledge Enhanced Primary Structure Modeling
Hong-Yu Zhou, Yunxiang Fu, Zhicheng Zhang +2
Protein representation learning has primarily benefited from the remarkable development of language models (LMs). Accordingly, pre-trained protein models also suffer from a problem…
Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation
Ruifei Zhang, Sishuo Liu, Yizhou Yu +1
Biomedical image segmentation plays a significant role in computer-aided diagnosis. However, existing CNN based methods rely heavily on massive manual annotations, which are very e…
Adaptive Context Selection for Polyp Segmentation
Ruifei Zhang, Guanbin Li, Zhen Li +3
Accurate polyp segmentation is of great significance for the diagnosis and treatment of colorectal cancer. However, it has always been very challenging due to the diverse shape and…
GraVIS: Grouping Augmented Views from Independent Sources for Dermatology Analysis
Hong-Yu Zhou, Chixiang Lu, Liansheng Wang +1
Self-supervised representation learning has been extremely successful in medical image analysis, as it requires no human annotations to provide transferable representations for dow…
Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation
Gangming Zhao, Kongming Liang, Chengwei Pan +4
Vessel segmentation is widely used to help with vascular disease diagnosis. Vessels reconstructed using existing methods are often not sufficiently accurate to meet clinical use st…
I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation
Haoyu Ma, Xiangru Lin, Yizhou Yu
Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level image stati…
PCRLv2: A Unified Visual Information Preservation Framework for Self-supervised Pre-training in Medical Image Analysis
Hong-Yu Zhou, Chixiang Lu, Chaoqi Chen +2
Recent advances in self-supervised learning (SSL) in computer vision are primarily comparative, whose goal is to preserve invariant and discriminative semantics in latent represent…