129 citations · 742 across the 38 of their papers we have counts for
39 papers
Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method
Tianyi Liu, Kejun Wu, Yi Wang +3
The past decade has witnessed great strides in video recovery by specialist technologies, like video inpainting, completion, and error concealment. However, they typically simulate…
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…
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…
A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarking
Shaohui Mei, Jiawei Lian, Xiaofei Wang +3
Deep neural networks (DNNs) have found widespread applications in interpreting remote sensing (RS) imagery. However, it has been demonstrated in previous works that DNNs are vulner…
A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings
Wenyang Liu, Yi Wang, Kejun Wu +2
File fragment classification (FFC) on small chunks of memory is essential in memory forensics and Internet security. Existing methods mainly treat file fragments as 1d byte signals…
Bitstream-Corrupted JPEG Images are Restorable: Two-stage Compensation and Alignment Framework for Image Restoration
Wenyang Liu, Yi Wang, Kim-Hui Yap +1
In this paper, we study a real-world JPEG image restoration problem with bit errors on the encrypted bitstream. The bit errors bring unpredictable color casts and block shifts on d…
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.…
PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles
Andrea Piazzoni, Jim Cherian, Justin Dauwels +1
Even though virtual testing of Autonomous Vehicles (AVs) has been well recognized as essential for safety assessment, AV simulators are still undergoing active development. One par…
CoPEM: Cooperative Perception Error Models for Autonomous Driving
Andrea Piazzoni, Jim Cherian, Roshan Vijay +2
In this paper, we introduce the notion of Cooperative Perception Error Models (coPEMs) towards achieving an effective and efficient integration of V2X solutions within a virtual te…
TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Crowd Counting
Haihan Tang, Yi Wang, Lap-Pui Chau
In this paper, we propose a three-stream adaptive fusion network named TAFNet, which uses paired RGB and thermal images for crowd counting. Specifically, TAFNet is divided into one…
Low-Light Image Enhancement with Normalizing Flow
Yufei Wang, Renjie Wan, Wenhan Yang +3
To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them is one-to-many. Previous works based on the pixel-wise r…
Variational Disentanglement for Domain Generalization
Yufei Wang, Haoliang Li, Hao Cheng +3
Domain generalization aims to learn an invariant model that can generalize well to the unseen target domain. In this paper, we propose to tackle the problem of domain generalizatio…
Attention-Guided Progressive Neural Texture Fusion for High Dynamic Range Image Restoration
Jie Chen, Zaifeng Yang, Tsz Nam Chan +3
High Dynamic Range (HDR) imaging via multi-exposure fusion is an important task for most modern imaging platforms. In spite of recent developments in both hardware and algorithm in…
Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation
Yufei Wang, Haoliang Li, Lap-pui Chau +1
Though convolutional neural networks are widely used in different tasks, lack of generalization capability in the absence of sufficient and representative data is one of the challe…
Weakly-supervised Part-Attention and Mentored Networks for Vehicle Re-Identification
Lisha Tang, Yi Wang, Lap-Pui Chau
Vehicle re-identification (Re-ID) aims to retrieve images with the same vehicle ID across different cameras. Current part-level feature learning methods typically detect vehicle pa…
PDPGD: Primal-Dual Proximal Gradient Descent Adversarial Attack
Alexander Matyasko, Lap-Pui Chau
State-of-the-art deep neural networks are sensitive to small input perturbations. Since the discovery of this intriguing vulnerability, many defence methods have been proposed that…
Multi-object Tracking with Tracked Object Bounding Box Association
Nanyang Yang, Yi Wang, Lap-Pui Chau
The CenterTrack tracking algorithm achieves state-of-the-art tracking performance using a simple detection model and single-frame spatial offsets to localize objects and predict th…
Moving Towards Centers: Re-ranking with Attention and Memory for Re-identification
Yunhao Zhou, Yi Wang, Lap-Pui Chau
Re-ranking utilizes contextual information to optimize the initial ranking list of person or vehicle re-identification (re-ID), which boosts the retrieval performance at post-proce…
Dense Point Prediction: A Simple Baseline for Crowd Counting and Localization
Yi Wang, Xinyu Hou, Lap-Pui Chau
In this paper, we propose a simple yet effective crowd counting and localization network named SCALNet. Unlike most existing works that separate the counting and localization tasks…
Rethinking and Designing a High-performing Automatic License Plate Recognition Approach
Yi Wang, Zhen-Peng Bian, Yunhao Zhou +1
In this paper, we propose a real-time and accurate automatic license plate recognition (ALPR) approach. Our study illustrates the outstanding design of ALPR with four insights: (1)…
Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems
Haoliang Li, Yufei Wang, Xiaofei Xie +5
Deep neural networks (DNN) have shown great success in many computer vision applications. However, they are also known to be susceptible to backdoor attacks. When conducting backdo…
Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures
Mantang Guo, Junhui Hou, Jing Jin +2
Coded aperture is a promising approach for capturing the 4-D light field (LF), in which the 4-D data are compressively modulated into 2-D coded measurements that are further decode…
A Self-Training Approach for Point-Supervised Object Detection and Counting in Crowds
Yi Wang, Junhui Hou, Xinyu Hou +1
In this paper, we propose a novel self-training approach named Crowd-SDNet that enables a typical object detector trained only with point-level annotations (i.e., objects are label…