786 citations · 7.3k across the 175 of their papers we have counts for
61 papers · 1 filter
GuidedMix-Net: Semi-supervised Semantic Segmentation by Using Labeled Images as Reference
Peng Tu, Yawen Huang, Feng Zheng +3
Semi-supervised learning is a challenging problem which aims to construct a model by learning from limited labeled examples. Numerous methods for this task focus on utilizing the p…
Generative Kernel Continual learning
Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao +1
Kernel continual learning by \citet{derakhshani2021kernel} has recently emerged as a strong continual learner due to its non-parametric ability to tackle task interference and cata…
TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning
Shiming Chen, Ziming Hong, Wenjin Hou +6
Zero-shot learning (ZSL) tackles the novel class recognition problem by transferring semantic knowledge from seen classes to unseen ones. Existing attention-based models have strug…
Hierarchical Variational Memory for Few-shot Learning Across Domains
Yingjun Du, Xiantong Zhen, Ling Shao +1
Neural memory enables fast adaptation to new tasks with just a few training samples. Existing memory models store features only from the single last layer, which does not generaliz…
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning
Shiming Chen, Guo-Sen Xie, Yang Liu +5
Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable knowledge…
Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance
Nian Liu, Wangbo Zhao, Dingwen Zhang +2
The application of light field data in salient object de-tection is becoming increasingly popular recently. The diffi-culty lies in how to effectively fuse the features within the…
Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
Ni Zhang, Junwei Han, Nian Liu +1
Humans perform co-saliency detection by first summarizing the consensus knowledge in the whole group and then searching corresponding objects in each image. Previous methods usuall…
Full-Duplex Strategy for Video Object Segmentation
Ge-Peng Ji, Deng-Ping Fan, Keren Fu +3
Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across thes…
Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation
Hongjun Chen, Jinbao Wang, Hong Cai Chen +4
Annotation burden has become one of the biggest barriers to semantic segmentation. Approaches based on click-level annotations have therefore attracted increasing attention due to…
Discriminative Region-based Multi-Label Zero-Shot Learning
Sanath Narayan, Akshita Gupta, Salman Khan +3
Multi-label zero-shot learning (ZSL) is a more realistic counter-part of standard single-label ZSL since several objects can co-exist in a natural image. However, the occurrence of…
From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder
Jiale Li, Hang Dai, Ling Shao +1
In this paper, we present an Intersection-over-Union (IoU) guided two-stage 3D object detector with a voxel-to-point decoder. To preserve the necessary information from all raw poi…
Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstruction
Fang Zhao, Wenhao Wang, Shengcai Liao +1
While single-view 3D reconstruction has made significant progress benefiting from deep shape representations in recent years, garment reconstruction is still not solved well due to…
FREE: Feature Refinement for Generalized Zero-Shot Learning
Shiming Chen, Wenjie Wang, Beihao Xia +4
Generalized zero-shot learning (GZSL) has achieved significant progress, with many efforts dedicated to overcoming the problems of visual-semantic domain gap and seen-unseen bias.…
Variational Topic Inference for Chest X-Ray Report Generation
Ivona Najdenkoska, Xiantong Zhen, Marcel Worring +1
Automating report generation for medical imaging promises to reduce workload and assist diagnosis in clinical practice. Recent work has shown that deep learning models can successf…
Kernel Continual Learning
Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao +1
This paper introduces kernel continual learning, a simple but effective variant of continual learning that leverages the non-parametric nature of kernel methods to tackle catastrop…
Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains
Shivam Chandhok, Sanath Narayan, Hisham Cholakkal +4
The need to address the scarcity of task-specific annotated data has resulted in concerted efforts in recent years for specific settings such as zero-shot learning (ZSL) and domain…
Local-to-Global Self-Attention in Vision Transformers
Jinpeng Li, Yichao Yan, Shengcai Liao +2
Transformers have demonstrated great potential in computer vision tasks. To avoid dense computations of self-attentions in high-resolution visual data, some recent Transformer mode…
Instance-Level Relative Saliency Ranking with Graph Reasoning
Nian Liu, Long Li, Wangbo Zhao +2
Conventional salient object detection models cannot differentiate the importance of different salient objects. Recently, two works have been proposed to detect saliency ranking by…
GuidedMix-Net: Learning to Improve Pseudo Masks Using Labeled Images as Reference
Peng Tu, Yawen Huang, Rongrong Ji +2
Semi-supervised learning is a challenging problem which aims to construct a model by learning from a limited number of labeled examples. Numerous methods have been proposed to tack…
Sparse Needlets for Lighting Estimation with Spherical Transport Loss
Fangneng Zhan, Changgong Zhang, Wenbo Hu +4
Accurate lighting estimation is challenging yet critical to many computer vision and computer graphics tasks such as high-dynamic-range (HDR) relighting. Existing approaches model…
DONet: Dual-Octave Network for Fast MR Image Reconstruction
Chun-Mei Feng, Zhanyuan Yang, Huazhu Fu +3
Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration has long been the subject of research. This is commonly achieved by obtaining multi…
AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection
Hongsong Wang, Shengcai Liao, Ling Shao
Unsupervised domain adaptation for object detection is a challenging problem with many real-world applications. Unfortunately, it has received much less attention than supervised o…
When Liebig's Barrel Meets Facial Landmark Detection: A Practical Model
Haibo Jin, Jinpeng Li, Shengcai Liao +1
In recent years, significant progress has been made in the research of facial landmark detection. However, few prior works have thoroughly discussed about models for practical appl…
Exploring Visual Context for Weakly Supervised Person Search
Yichao Yan, Jinpeng Li, Shengcai Liao +4
Person search has recently emerged as a challenging task that jointly addresses pedestrian detection and person re-identification. Existing approaches follow a fully supervised set…