105 citations · 433 across the 42 of their papers we have counts for
24 papers · 1 filter
Order-preserving Consistency Regularization for Domain Adaptation and Generalization
Mengmeng Jing, Xiantong Zhen, Jingjing Li +1
Deep learning models fail on cross-domain challenges if the model is oversensitive to domain-specific attributes, e.g., lightning, background, camera angle, etc. To alleviate this…
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models
Baoshuo Kan, Teng Wang, Wenpeng Lu +3
Pre-trained vision-language models, e.g., CLIP, working with manually designed prompts have demonstrated great capacity of transfer learning. Recently, learnable prompts achieve st…
Lightweight Improved Residual Network for Efficient Inverse Tone Mapping
Liqi Xue, Tianyi Xu, Yongbao Song +4
The display devices like HDR10 televisions are increasingly prevalent in our daily life for visualizing high dynamic range (HDR) images. But the majority of media images on the int…
CageViT: Convolutional Activation Guided Efficient Vision Transformer
Hao Zheng, Jinbao Wang, Xiantong Zhen +3
Recently, Transformers have emerged as the go-to architecture for both vision and language modeling tasks, but their computational efficiency is limited by the length of the input…
SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail
Yingjun Du, Jiayi Shen, Xiantong Zhen +1
Modern image classifiers perform well on populated classes, while degrading considerably on tail classes with only a few instances. Humans, by contrast, effortlessly handle the lon…
Implicit Diffusion Models for Continuous Super-Resolution
Sicheng Gao, Xuhui Liu, Bohan Zeng +6
Image super-resolution (SR) has attracted increasing attention due to its wide applications. However, current SR methods generally suffer from over-smoothing and artifacts, and mos…
Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning
Ivona Najdenkoska, Xiantong Zhen, Marcel Worring
Multimodal few-shot learning is challenging due to the large domain gap between vision and language modalities. Existing methods are trying to communicate visual concepts as prompt…
CK-Transformer: Commonsense Knowledge Enhanced Transformers for Referring Expression Comprehension
Zhi Zhang, Helen Yannakoudakis, Xiantong Zhen +1
The task of multimodal referring expression comprehension (REC), aiming at localizing an image region described by a natural language expression, has recently received increasing a…
Probabilistic Integration of Object Level Annotations in Chest X-ray Classification
Tom van Sonsbeek, Xiantong Zhen, Dwarikanath Mahapatra +1
Medical image datasets and their annotations are not growing as fast as their equivalents in the general domain. This makes translation from the newest, more data-intensive methods…
Association Graph Learning for Multi-Task Classification with Category Shifts
Jiayi Shen, Zehao Xiao, Xiantong Zhen +2
In this paper, we focus on multi-task classification, where related classification tasks share the same label space and are learned simultaneously. In particular, we tackle a new s…
Joint Super-Resolution and Inverse Tone-Mapping: A Feature Decomposition Aggregation Network and A New Benchmark
Gang Xu, Yu-chen Yang, Liang Wang +2
Joint Super-Resolution and Inverse Tone-Mapping (joint SR-ITM) aims to increase the resolution and dynamic range of low-resolution and standard dynamic range images. Recent network…
LifeLonger: A Benchmark for Continual Disease Classification
Mohammad Mahdi Derakhshani, Ivona Najdenkoska, Tom van Sonsbeek +4
Deep learning models have shown a great effectiveness in recognition of findings in medical images. However, they cannot handle the ever-changing clinical environment, bringing new…
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…
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…
Attentional Prototype Inference for Few-Shot Segmentation
Haoliang Sun, Xiankai Lu, Haochen Wang +4
This paper aims to address few-shot segmentation. While existing prototype-based methods have achieved considerable success, they suffer from uncertainty and ambiguity caused by li…
Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression
Haoliang Sun, Xiantong Zhen, Chris Bailey +3
The Cobb angle that quantitatively evaluates the spinal curvature plays an important role in the scoliosis diagnosis and treatment. Conventional measurement of these angles suffers…
Learning to Learn with Variational Information Bottleneck for Domain Generalization
Yingjun Du, Jun Xu, Huan Xiong +4
Domain generalization models learn to generalize to previously unseen domains, but suffer from prediction uncertainty and domain shift. In this paper, we address both problems. We…
Conditional Variational Image Deraining
Ying-Jun Du, Jun Xu, Xian-Tong Zhen +2
Image deraining is an important yet challenging image processing task. Though deterministic image deraining methods are developed with encouraging performance, they are infeasible…
Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
Xiaolong Jiang, Peizhao Li, Yanjing Li +1
In this work, we present an end-to-end framework to settle data association in online Multiple-Object Tracking (MOT). Given detection responses, we formulate the frame-by-frame dat…
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network
Xiaolong Jiang, Zehao Xiao, Baochang Zhang +4
Crowd counting has recently attracted increasing interest in computer vision but remains a challenging problem. In this paper, we propose a trellis encoder-decoder network (TEDnet)…
Two-Stream Multi-Task Network for Fashion Recognition
Peizhao Li, Yanjing Li, Xiaolong Jiang +1
In this paper, we present a two-stream multi-task network for fashion recognition. This task is challenging as fashion clothing always contain multiple attributes, which need to be…
Model-free Tracking with Deep Appearance and Motion Features Integration
Xiaolong Jiang, Peizhao Li, Xiantong Zhen +1
Being able to track an anonymous object, a model-free tracker is comprehensively applicable regardless of the target type. However, designing such a generalized framework is challe…
In Defense of Single-column Networks for Crowd Counting
Ze Wang, Zehao Xiao, Kai Xie +3
Crowd counting usually addressed by density estimation becomes an increasingly important topic in computer vision due to its widespread applications in video surveillance, urban pl…
Towards Direct Medical Image Analysis without Segmentation
Xiantong Zhen, Shuo Li
Direct methods have recently emerged as an effective and efficient tool in automated medical image analysis and become a trend to solve diverse challenging tasks in clinical practi…