262 citations · 1.7k across the 63 of their papers we have counts for
63 papers
Coding for Intelligence from the Perspective of Category
Wenhan Yang, Zixuan Hu, Lilang Lin +2
Coding, which targets compressing and reconstructing data, and intelligence, often regarded at an abstract computational level as being centered around model learning and predictio…
Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder
Yiyang Ma, Wenhan Yang, Jiaying Liu
The images produced by diffusion models can attain excellent perceptual quality. However, it is challenging for diffusion models to guarantee distortion, hence the integration of d…
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing Imagery
Jialu Sui, Yiyang Ma, Wenhan Yang +3
The presence of cloud layers severely compromises the quality and effectiveness of optical remote sensing (RS) images. However, existing deep-learning (DL)-based Cloud Removal (CR)…
ExposureDiffusion: Learning to Expose for Low-light Image Enhancement
Yufei Wang, Yi Yu, Wenhan Yang +4
Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed…
Enhancing Low-Light Images Using Infrared-Encoded Images
Shulin Tian, Yufei Wang, Renjie Wan +3
Low-light image enhancement task is essential yet challenging as it is ill-posed intrinsically. Previous arts mainly focus on the low-light images captured in the visible spectrum…
Similarity Min-Max: Zero-Shot Day-Night Domain Adaptation
Rundong Luo, Wenjing Wang, Wenhan Yang +1
Low-light conditions not only hamper human visual experience but also degrade the model's performance on downstream vision tasks. While existing works make remarkable progress on d…
Beyond Learned Metadata-based Raw Image Reconstruction
Yufei Wang, Yi Yu, Wenhan Yang +4
While raw images have distinct advantages over sRGB images, e.g., linearity and fine-grained quantization levels, they are not widely adopted by general users due to their substant…
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
Yiyang Ma, Huan Yang, Wenhan Yang +2
Diffusion models, as a kind of powerful generative model, have given impressive results on image super-resolution (SR) tasks. However, due to the randomness introduced in the rever…
Robust Contrastive Language-Image Pre-training against Data Poisoning and Backdoor Attacks
Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
Contrastive vision-language representation learning has achieved state-of-the-art performance for zero-shot classification, by learning from millions of image-caption pairs crawled…
Graph Contrastive Learning under Heterophily via Graph Filters
Wenhan Yang, Baharan Mirzasoleiman
Graph contrastive learning (CL) methods learn node representations in a self-supervised manner by maximizing the similarity between the augmented node representations obtained via…
Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger
Yi Yu, Yufei Wang, Wenhan Yang +3
Recent deep-learning-based compression methods have achieved superior performance compared with traditional approaches. However, deep learning models have proven to be vulnerable t…
Raw Image Reconstruction with Learned Compact Metadata
Yufei Wang, Yi Yu, Wenhan Yang +4
While raw images exhibit advantages over sRGB images (e.g., linearity and fine-grained quantization level), they are not widely used by common users due to the large storage requir…
Removing Image Artifacts From Scratched Lens Protectors
Yufei Wang, Renjie Wan, Wenhan Yang +3
A protector is placed in front of the camera lens for mobile devices to avoid damage, while the protector itself can be easily scratched accidentally, especially for plastic ones.…
Gap-closing Matters: Perceptual Quality Evaluation and Optimization of Low-Light Image Enhancement
Baoliang Chen, Lingyu Zhu, Hanwei Zhu +3
There is a growing consensus in the research community that the optimization of low-light image enhancement approaches should be guided by the visual quality perceived by end users…
ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal
Lanqing Guo, Chong Wang, Wenhan Yang +4
Recent deep learning methods have achieved promising results in image shadow removal. However, their restored images still suffer from unsatisfactory boundary artifacts, due to the…
Estimating Reflectance Layer from A Single Image: Integrating Reflectance Guidance and Shadow/Specular Aware Learning
Yeying Jin, Ruoteng Li, Wenhan Yang +1
Estimating the reflectance layer from a single image is a challenging task. It becomes more challenging when the input image contains shadows or specular highlights, which often re…
DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity
Yeying Jin, Wei Ye, Wenhan Yang +2
Removing soft and self shadows that lack clear boundaries from a single image is still challenging. Self shadows are shadows that are cast on the object itself. Most existing metho…
Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal
Yeying Jin, Wending Yan, Wenhan Yang +1
Few existing image defogging or dehazing methods consider dense and non-uniform particle distributions, which usually happen in smoke, dust and fog. Dealing with these dense and/or…
Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cues
Zitong Yu, Rizhao Cai, Zhi Li +3
Face anti-spoofing (FAS) and face forgery detection play vital roles in securing face biometric systems from presentation attacks (PAs) and vicious digital manipulation (e.g., deep…
Meta-Interpolation: Time-Arbitrary Frame Interpolation via Dual Meta-Learning
Shixing Yu, Yiyang Ma, Wenhan Yang +2
Existing video frame interpolation methods can only interpolate the frame at a given intermediate time-step, e.g. 1/2. In this paper, we aim to explore a more generalized kind of v…
Cycle-Interactive Generative Adversarial Network for Robust Unsupervised Low-Light Enhancement
Zhangkai Ni, Wenhan Yang, Hanli Wang +3
Getting rid of the fundamental limitations in fitting to the paired training data, recent unsupervised low-light enhancement methods excel in adjusting illumination and contrast of…
Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression
Yeying Jin, Wenhan Yang, Robby T. Tan
Night images suffer not only from low light, but also from uneven distributions of light. Most existing night visibility enhancement methods focus mainly on enhancing low-light reg…
Feature-Aligned Video Raindrop Removal with Temporal Constraints
Wending Yan, Lu Xu, Wenhan Yang +1
Existing adherent raindrop removal methods focus on the detection of the raindrop locations, and then use inpainting techniques or generative networks to recover the background beh…
UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning
Yongzhen Wang, Xuefeng Yan, Fu Lee Wang +4
While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known d…