277 citations · 1.7k across the 70 of their papers we have counts for
44 papers · 1 filter
MedVision: Benchmarking Quantitative Medical Image Analysis
Yongcheng Yao, Yongshuo Zong, Raman Dutt +3
Current vision-language models (VLMs) in medicine are primarily designed for categorical question answering (e.g., "Is this normal or abnormal?") or qualitative descriptive tasks.…
Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration
Junyuan Deng, Xinyi Wu, Yongxing Yang +3
Recently, pre-trained text-to-image (T2I) models have been extensively adopted for real-world image restoration because of their powerful generative prior. However, controlling the…
Generating Compositional Scenes via Text-to-image RGBA Instance Generation
Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang +2
Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditio…
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation
Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang +5
Text-to-image generation has achieved astonishing results, yet precise spatial controllability and prompt fidelity remain highly challenging. This limitation is typically addressed…
Optimisation-Based Multi-Modal Semantic Image Editing
Bowen Li, Yongxin Yang, Steven McDonagh +3
Image editing affords increased control over the aesthetics and content of generated images. Pre-existing works focus predominantly on text-based instructions to achieve desired im…
Learning to Name Classes for Vision and Language Models
Sarah Parisot, Yongxin Yang, Steven McDonagh
Large scale vision and language models can achieve impressive zero-shot recognition performance by mapping class specific text queries to image content. Two distinct challenges tha…
Label-Efficient Object Detection via Region Proposal Network Pre-Training
Nanqing Dong, Linus Ericsson, Yongxin Yang +2
Self-supervised pre-training, based on the pretext task of instance discrimination, has fueled the recent advance in label-efficient object detection. However, existing studies foc…
Fine-Grained VR Sketching: Dataset and Insights
Ling Luo, Yulia Gryaditskaya, Yongxin Yang +2
We present the first fine-grained dataset of 1,497 3D VR sketch and 3D shape pairs of a chair category with large shapes diversity. Our dataset supports the recent trend in the ske…
Towards 3D VR-Sketch to 3D Shape Retrieval
Ling Luo, Yulia Gryaditskaya, Yongxin Yang +2
Growing free online 3D shapes collections dictated research on 3D retrieval. Active debate has however been had on (i) what the best input modality is to trigger retrieval, and (ii…
Long-tail Recognition via Compositional Knowledge Transfer
Sarah Parisot, Pedro M. Esperanca, Steven McDonagh +3
In this work, we introduce a novel strategy for long-tail recognition that addresses the tail classes' few-shot problem via training-free knowledge transfer. Our objective is to tr…
Domain Attention Consistency for Multi-Source Domain Adaptation
Zhongying Deng, Kaiyang Zhou, Yongxin Yang +1
Most existing multi-source domain adaptation (MSDA) methods minimize the distance between multiple source-target domain pairs via feature distribution alignment, an approach borrow…
MixStyle Neural Networks for Domain Generalization and Adaptation
Kaiyang Zhou, Yongxin Yang, Yu Qiao +1
Neural networks do not generalize well to unseen data with domain shifts -- a longstanding problem in machine learning and AI. To overcome the problem, we propose MixStyle, a simpl…
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images
Nanqing Dong, Matteo Maggioni, Yongxin Yang +3
This paper is concerned with contrastive learning (CL) for low-level image restoration and enhancement tasks. We propose a new label-efficient learning paradigm based on residuals,…
Towards Unsupervised Sketch-based Image Retrieval
Conghui Hu, Yongxin Yang, Yunpeng Li +2
The practical value of existing supervised sketch-based image retrieval (SBIR) algorithms is largely limited by the requirement for intensive data collection and labeling. In this…
Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao +1
Though convolutional neural networks (CNNs) have demonstrated remarkable ability in learning discriminative features, they often generalize poorly to unseen domains. Domain general…
StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval
Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang +2
Sketch-based image retrieval (SBIR) is a cross-modal matching problem which is typically solved by learning a joint embedding space where the semantic content shared between photo…
Cloud2Curve: Generation and Vectorization of Parametric Sketches
Ayan Das, Yongxin Yang, Timothy Hospedales +2
Analysis of human sketches in deep learning has advanced immensely through the use of waypoint-sequences rather than raster-graphic representations. We further aim to model sketche…
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain +3
A fundamental challenge faced by existing Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) models is the data scarcity -- model performances are largely bottlenecked by the lack…
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting
Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang +3
Self-supervised learning has gained prominence due to its efficacy at learning powerful representations from unlabelled data that achieve excellent performance on many challenging…
Context-Aware Layout to Image Generation with Enhanced Object Appearance
Sen He, Wentong Liao, Michael Ying Yang +4
A layout to image (L2I) generation model aims to generate a complicated image containing multiple objects (things) against natural background (stuff), conditioned on a given layout…
Tensor Composition Net for Visual Relationship Prediction
Yuting Qiang, Yongxin Yang, Xueting Zhang +2
We present a novel Tensor Composition Net (TCN) to predict visual relationships in images. Visual Relationship Prediction (VRP) provides a more challenging test of image understand…
Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval
Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang +2
Sketch as an image search query is an ideal alternative to text in capturing the fine-grained visual details. Prior successes on fine-grained sketch-based image retrieval (FG-SBIR)…
BézierSketch: A generative model for scalable vector sketches
Ayan Das, Yongxin Yang, Timothy Hospedales +2
The study of neural generative models of human sketches is a fascinating contemporary modeling problem due to the links between sketch image generation and the human drawing proces…
Learning to Generate Novel Domains for Domain Generalization
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales +1
This paper focuses on domain generalization (DG), the task of learning from multiple source domains a model that generalizes well to unseen domains. A main challenge for DG is that…