3 citations · 3 across the 12 of their papers we have counts for
13 papers
Principled Reflection Separation via Nonlinear Superposition and Feature Interaction
Qiming Hu, Mingjia Li, Yuntong Li +1
Single-image reflection separation is fundamentally challenged by the entanglement of transmission and reflection layers under complex image formation processes. Existing approache…
Internally Referenced Low-Light Enhancement
Peiyuan He, Hainuo Wang, Hengxing Liu +2
Self-supervised low-light image enhancement (LLIE) is highly appealing as it eliminates the reliance on external paired data. However, the lack of external references causes networ…
Representative Attention For Vision Transformers
Yuntong Li, Hainuo Wang, Hengxing Liu +2
Linear attention has emerged as a promising direction for scaling Vision Transformers beyond the quadratic cost of dense self-attention. A prevalent strategy is to compress spatial…
On the Global Photometric Alignment for Low-Level Vision
Mingjia Li, Tianle Du, Hainuo Wang +2
Supervised low-level vision models rely on pixel-wise losses against paired references, yet paired training sets exhibit per-pair photometric inconsistency, say, different image pa…
Anchor then Polish for Low-light Enhancement
Tianle Du, Mingjia Li, Hainuo Wang +1
Low-light image enhancement is challenging due to entangled degradations, mainly including poor illumination, color shifts, and texture interference. Existing methods often rely on…
WiT: Waypoint Diffusion Transformers for Alleviating Trajectory Conflict in Pixel-Space Image Generation
Hainuo Wang, Mingjia Li, Xiaojie Guo
While recent Flow Matching models avoid the reconstruction bottlenecks of latent autoencoders by operating directly in pixel space, the raw pixel manifold provides little explicit…
Rectifying Latent Space for Generative Single-Image Reflection Removal
Mingjia Li, Jin Hu, Hainuo Wang +3
Single-image reflection removal is a highly ill-posed problem, where existing methods struggle to reason about the composition of corrupted regions, causing them to fail at recover…
NTIRE 2025 Image Shadow Removal Challenge Report
Florin-Alexandru Vasluianu, Tim Seizinger, Zhuyun Zhou +79
This work examines the findings of the NTIRE 2025 Shadow Removal Challenge. A total of 306 participants have registered, with 17 teams successfully submitting their solutions durin…
ShadowHack: Hacking Shadows via Luminance-Color Divide and Conquer
Jin Hu, Mingjia Li, Xiaojie Guo
Shadows introduce challenges such as reduced brightness, texture deterioration, and color distortion in images, complicating a holistic solution. This study presents \textbf{Shadow…
Regional Attention for Shadow Removal
Hengxing Liu, Mingjia Li, Xiaojie Guo
Shadow, as a natural consequence of light interacting with objects, plays a crucial role in shaping the aesthetics of an image, which however also impairs the content visibility an…
LIME-Eval: Rethinking Low-light Image Enhancement Evaluation via Object Detection
Mingjia Li, Hao Zhao, Xiaojie Guo
Due to the nature of enhancement--the absence of paired ground-truth information, high-level vision tasks have been recently employed to evaluate the performance of low-light image…
Reversible Decoupling Network for Single Image Reflection Removal
Hao Zhao, Mingjia Li, Qiming Hu +1
Recent deep-learning-based approaches to single-image reflection removal have shown promising advances, primarily for two reasons: 1) the utilization of recognition-pretrained feat…
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Ao Li +109
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective netw…