355 citations · 2.7k across the 325 of their papers we have counts for
51 papers · 2 filters
Experts-Guided Unbalanced Optimal Transport for ISP Learning from Unpaired and/or Paired Data
Georgy Perevozchikov, Nancy Mehta, Egor Ershov +1
Learned Image Signal Processing (ISP) pipelines offer powerful end-to-end performance but are critically dependent on large-scale paired raw-to-sRGB datasets. This reliance on cost…
Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design
Raghuvir Duvvuri, Chandini Vysyaraju, Avi Goyal +2
Automated neural network architecture design remains a significant challenge in computer vision. Task diversity and computational constraints require both effective architectures a…
A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks
Waleed Khalid, Dmitry Ignatov, Radu Timofte
Reusing existing neural-network components is central to research efficiency, yet discovering, extracting, and validating such modules across thousands of open-source repositories…
Layover or Direct Flight: Rethinking Audio-Guided Image Segmentation
Joel Alberto Santos, Zongwei Wu, Xavier Alameda-Pineda +1
Understanding human instructions is essential for enabling smooth human-robot interaction. In this work, we focus on object grounding, i.e., localizing an object of interest in a v…
Sequence-Adaptive Video Prediction in Continuous Streams using Diffusion Noise Optimization
Sina Mokhtarzadeh Azar, Emad Bahrami, Enrico Pallotta +3
In this work, we investigate diffusion-based video prediction models, which forecast future video frames, for continuous video streams. In this context, the models observe continuo…
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…
Efficient Real-World Deblurring using Single Images: AIM 2025 Challenge Report
Daniel Feijoo, Paula Garrido-Mellado, Marcos V. Conde +4
This paper reviews the AIM 2025 Efficient Real-World Deblurring using Single Images Challenge, which aims to advance in efficient real-blur restoration. The challenge is based on a…
Efficient Perceptual Image Super Resolution: AIM 2025 Study and Benchmark
Bruno Longarela, Marcos V. Conde, Alvaro Garcia +1
This paper presents a comprehensive study and benchmark on Efficient Perceptual Super-Resolution (EPSR). While significant progress has been made in efficient PSNR-oriented super r…
AIM 2025 Challenge on Real-World RAW Image Denoising
Feiran Li, Jiacheng Li, Marcos V. Conde +4
We introduce the AIM 2025 Real-World RAW Image Denoising Challenge, aiming to advance efficient and effective denoising techniques grounded in data synthesis. The competition is bu…
Cat: Post-Training Quantization Error Reduction via Cluster-based Affine Transformation
Ali Zoljodi, Radu Timofte, Masoud Daneshtalab
Post-Training Quantization (PTQ) reduces the memory footprint and computational overhead of deep neural networks by converting full-precision (FP) values into quantized and compres…
AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results
Chao Wang, Francesco Banterle, Bin Ren +25
This paper presents a comprehensive review of the AIM 2025 Challenge on Inverse Tone Mapping (ITM). The challenge aimed to push forward the development of effective ITM algorithms…
MIORe & VAR-MIORe: Benchmarks to Push the Boundaries of Restoration
George Ciubotariu, Zhuyun Zhou, Zongwei Wu +1
We introduce MIORe and VAR-MIORe, two novel multi-task datasets that address critical limitations in current motion restoration benchmarks. Designed with high-frame-rate (1000 FPS)…
AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
George Ciubotariu, Florin-Alexandru Vasluianu, Zhuyun Zhou +44
This paper presents a comprehensive review of the AIM 2025 High FPS Non-Uniform Motion Deblurring Challenge, highlighting the proposed solutions and final results. The objective of…
Degradation-Aware All-in-One Image Restoration via Latent Prior Encoding
S M A Sharif, Abdur Rehman, Fayaz Ali Dharejo +2
Real-world images often suffer from spatially diverse degradations such as haze, rain, snow, and low-light, significantly impacting visual quality and downstream vision tasks. Exis…
WaveHiT-SR: Hierarchical Wavelet Network for Efficient Image Super-Resolution
Fayaz Ali, Muhammad Zawish, Steven Davy +1
Transformers have demonstrated promising performance in computer vision tasks, including image super-resolution (SR). The quadratic computational complexity of window self-attentio…
The Return of Structural Handwritten Mathematical Expression Recognition
Jakob Seitz, Tobias Lengfeld, Radu Timofte
Handwritten Mathematical Expression Recognition is foundational for educational technologies, enabling applications like digital note-taking and automated grading. While modern enc…
AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
Alexander Yakovenko, George Chakvetadze, Ilya Khrapov +17
This paper reviews the AIM 2025 (Advances in Image Manipulation) Low-Light RAW Video Denoising Challenge. The task is to develop methods that denoise low-light RAW video by exploit…
DiTVR: Zero-Shot Diffusion Transformer for Video Restoration
Sicheng Gao, Nancy Mehta, Zongwei Wu +1
Video restoration aims to reconstruct high quality video sequences from low quality inputs, addressing tasks such as super resolution, denoising, and deblurring. Traditional regres…
After the Party: Navigating the Mapping From Color to Ambient Lighting
Florin-Alexandru Vasluianu, Tim Seizinger, Zongwei Wu +1
Illumination in practical scenarios is inherently complex, involving colored light sources, occlusions, and diverse material interactions that produce intricate reflectance and sha…
AIM 2025 Rip Current Segmentation (RipSeg) Challenge Report
Andrei Dumitriu, Florin Miron, Florin Tatui +24
This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentation in still images. Rip currents…
What You Have is What You Track: Adaptive and Robust Multimodal Tracking
Yuedong Tan, Jiawei Shao, Eduard Zamfir +7
Multimodal data is known to be helpful for visual tracking by improving robustness to appearance variations. However, sensor synchronization challenges often compromise data availa…
Modulate and Reconstruct: Learning Hyperspectral Imaging from Misaligned Smartphone Views
Daniil Reutsky, Daniil Vladimirov, Yasin Mamedov +4
Hyperspectral reconstruction (HSR) from RGB images is a highly promising direction for accurate color reproduction and material color measurement. While most existing approaches re…
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…
AugmentGest: Can Random Data Cropping Augmentation Boost Gesture Recognition Performance?
Nada Aboudeshish, Dmitry Ignatov, Radu Timofte
Data augmentation is a crucial technique in deep learning, particularly for tasks with limited dataset diversity, such as skeleton-based datasets. This paper proposes a comprehensi…