738 citations · 1.1k across the 85 of their papers we have counts for
98 papers
CRISP: Progressive Illumination Curriculum for Recurrent Low-Light Video Enhancement with Semantic Priors
Ruirui Lin, Xin Yan Lim, Yini Li +2
Low-light video enhancement requires the recovery of brightness, color, and fine spatial structures while preserving temporal coherence in the presence of noise and motion. Existin…
Separation of variables for coupled radiative perturbations of Kerr-Newman-de Sitter black holes
Daisuke Yoshida
We extend Hintz's separation of variables for radiative gravitational and electromagnetic perturbations from Kerr-Newman to Kerr-Newman-de Sitter black holes. On subextremal backgr…
Golden Anchor for Video Generation
Jinyuan Xu, Shitong Shao, Lichen Bai +4
Video generation supports digital content creation, with applications in virtual avatars, AI-driven filmmaking, interactive game engines, and world models. State-of-the-art systems…
Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors
Ge Gao, Siyue Teng, Chanqgi Wang +5
Immersive video communication requires photorealistic, render-efficient, and compact dynamic scene representations. 3D Gaussian Splatting (3DGS) offers a promising representation,…
OceanXL: Large-scale Underwater 3D Gaussian Splatting via Block Partitioning and Adaptive Pruning
Haoran Wang, Shaoyu Cai, Adrian Azzarelli +7
Underwater 3D reconstruction is critical for marine exploration, ecological monitoring, and subsea infrastructure inspection, yet remains challenging at large scale due to light at…
WaveDINO: Learning-Based Atmospheric Correction of Unwrapped InSAR Interferograms Validated by GNSS: Results at Laguna del Maule and Campi Flegrei Volcanoes
Robert Popescu, Juliet Biggs, Tianyuan Zhu +1
Interferometric Synthetic Aperture Radar (InSAR) enables effective monitoring of volcanic deformation; however, the observed signals are often corrupted by atmospheric phase delays…
ReMATF: Recurrent Motion-Adaptive Multi-scale Turbulence Mitigation for Dynamic Scenes
Zhiming Liu, Zhicheng Zou, Nantheera Anantrasirichai
Atmospheric turbulence severely degrades video quality by introducing distortions such as geometric warping, blur, and temporal flickering, posing significant challenges to both vi…
Relightable Gaussian Splatting for Virtual Production Using Image-Based Illumination
Adrian Azzarelli, Nantheera Anantrasirichai, James Pollock +1
Virtual production (VP) use LED walls to provide both background imagery and image-based lighting. While this enables on-set compositing, it couples lighting to background and scen…
PixIE: Prompted Pixel-Space Low-Light Image Enhancement
Ruirui Lin, Guoxi Huang, David Bull +1
Low-light images suffer from severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We propose PixIE, a feed-forw…
BVI-Mamba: Video Enhancement Using a Visual State-Space Model for Low-Light and Underwater Environments
Guoxi Huang, Ruirui Lin, Yini Li +2
Videos captured in low-light and underwater conditions often suffer from distortions such as noise, low contrast, color imbalance, and blur. These issues not only limit visibility…
WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance
Xin Tian, Xudong Ma, Tianqi Yang +4
We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulties: (i) severe class imbalan…
Single Image Super-Resolution via Bivariate `A Trous Wavelet Diffusion
Maryam Heidari, Nantheera Anantrasirichai, Alin Achim
The effectiveness of super resolution (SR) models hinges on their ability to recover high frequency structure without introducing artifacts. Diffusion based approaches have recentl…
AWDiff: An a trous wavelet diffusion model for lung ultrasound image synthesis
Maryam Heidari, Nantheera Anantrasirichai, Steven Walker +2
Lung ultrasound (LUS) is a safe and portable imaging modality, but the scarcity of data limits the development of machine learning methods for image interpretation and disease moni…
An InSAR Phase Unwrapping Framework for Large-scale and Complex Events
Yijia Song, Juliet Biggs, Alin Achim +3
Phase unwrapping remains a critical and challenging problem in InSAR processing, particularly in scenarios involving complex deformation patterns. In earthquake-related deformation…
Prune Wisely, Reconstruct Sharply: Compact 3D Gaussian Splatting via Adaptive Pruning and Difference-of-Gaussian Primitives
Haoran Wang, Guoxi Huang, Fan Zhang +2
Recent significant advances in 3D scene representation have been driven by 3D Gaussian Splatting (3DGS), which has enabled real-time rendering with photorealistic quality. 3DGS oft…
PocketDVDNet: Realtime Video Denoising for Real Camera Noise
Crispian Morris, Imogen Dexter, Fan Zhang +2
Live video denoising under realistic, multi-component sensor noise remains challenging for applications such as autofocus, autonomous driving, and surveillance. We propose PocketDV…
Forest-Chat: Adapting Vision-Language Agents for Interactive Forest Change Analysis
James Brock, Ce Zhang, Nantheera Anantrasirichai
The increasing availability of high-resolution satellite imagery, together with advances in deep learning, creates new opportunities for forest monitoring workflows. Two central ch…
Vision-Language Agents for Interactive Forest Change Analysis
James Brock, Ce Zhang, Nantheera Anantrasirichai
Modern forest monitoring workflows increasingly benefit from the growing availability of high-resolution satellite imagery and advances in deep learning. Two persistent challenges…
UnwrapDiff: A Conditional Diffusion Model for InSAR Phase Unwrapping
Yijia Song, Juliet Biggs, Alin Achim +3
Phase unwrapping is a fundamental problem in InSAR data processing, supporting geophysical applications such as deformation monitoring and hazard assessment. Its reliability is lim…
ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark
Joanne Lin, Ruirui Lin, Yini Li +2
Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other adverse conditions. The lack of…
TempRetinex: Retinex-based Unsupervised Enhancement for Low-light Video Under Diverse Lighting Conditions
Yini Li, Louis Forster, David Bull +1
The acquisition of paired low-light video sequences remains challenging due to issues associated with poor temporal consistency, varying illumination characteristics and camera par…
Splatography: Sparse multi-view dynamic Gaussian Splatting for filmmaking challenges
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull
Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. How…
NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Florin-Alexandru Vasluianu +102
This paper presents a comprehensive review of the NTIRE 2025 Low-Light Image Enhancement (LLIE) Challenge, highlighting the proposed solutions and final outcomes. The objective of…
Dynamic Weight-based Temporal Aggregation for Low-light Video Enhancement Under Extreme Noise
Ruirui Lin, Guoxi Huang, Nantheera Anantrasirichai
Low-light video enhancement (LLVE) is challenging due to noise, low contrast, and color degradation. While learning-based methods enable fast inference, they often fail under heavy…