102 citations · 234 across the 46 of their papers we have counts for
47 papers
Benchmarking RAW and RGB Restoration in Image Signal Processors
Zihao Lu, Radu Timofte, Marcos V. Conde
Modern cameras transform RAW sensor measurements into sRGB images through an image signal processor (ISP). We benchmark two placements for blind restoration around a fixed ISP: (A)…
TabH2O: A Unified Foundation Model for Tabular Prediction
Pascal Pfeiffer, Dmitry Gordeev, Mathias Müller +6
We present TabH2O, a foundation model for tabular data that performs classification and regression in a single forward pass via in-context learning. TabH2O builds on the TabICL arc…
NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
Marcos V. Conde, Radu Timofte, Zihao Lu +36
This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-R…
RAW Image Reconstruction from RGB on Smartphones. NTIRE 2025 Challenge Report
Marcos V. Conde, Radu Timofte, Radu Berdan +30
Numerous low-level vision tasks operate in the RAW domain due to its linear properties, bit depth, and sensor designs. Despite this, RAW image datasets are scarce and more expensiv…
The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Lei Sun +143
This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep mode…
Bokehlicious: Photorealistic Bokeh Rendering with Controllable Apertures
Tim Seizinger, Florin-Alexandru Vasluianu, Marcos V. Conde +2
Bokeh rendering methods play a key role in creating the visually appealing, softly blurred backgrounds seen in professional photography. While recent learning-based approaches show…
INRetouch: Context Aware Implicit Neural Representation for Photography Retouching
Omar Elezabi, Marcos V. Conde, Zongwei Wu +1
Professional photo editing remains challenging, requiring extensive knowledge of imaging pipelines and significant expertise. While recent deep learning approaches, particularly st…
Toward Efficient Deep Blind RAW Image Restoration
Marcos V. Conde, Florin Vasluianu, Radu Timofte
Multiple low-vision tasks such as denoising, deblurring and super-resolution depart from RGB images and further reduce the degradations, improving the quality. However, modeling th…
AIM 2024 Challenge on Efficient Video Super-Resolution for AV1 Compressed Content
Marcos V Conde, Zhijun Lei, Wen Li +3
Video super-resolution (VSR) is a critical task for enhancing low-bitrate and low-resolution videos, particularly in streaming applications. While numerous solutions have been deve…
Compressed Depth Map Super-Resolution and Restoration: AIM 2024 Challenge Results
Marcos V. Conde, Florin-Alexandru Vasluianu, Jinhui Xiong +3
The increasing demand for augmented reality (AR) and virtual reality (VR) applications highlights the need for efficient depth information processing. Depth maps, essential for ren…
AIM 2024 Challenge on UHD Blind Photo Quality Assessment
Vlad Hosu, Marcos V. Conde, Lorenzo Agnolucci +3
We introduce the AIM 2024 UHD-IQA Challenge, a competition to advance the No-Reference Image Quality Assessment (NR-IQA) task for modern, high-resolution photos. The challenge is b…
Streaming Neural Images
Marcos V. Conde, Andy Bigos, Radu Timofte
Implicit Neural Representations (INRs) are a novel paradigm for signal representation that have attracted considerable interest for image compression. INRs offer unprecedented adva…
Extreme Compression of Adaptive Neural Images
Leo Hoshikawa, Marcos V. Conde, Takeshi Ohashi +1
Implicit Neural Representations (INRs) and Neural Fields are a novel paradigm for signal representation, from images and audio to 3D scenes and videos. The fundamental idea is to r…
Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey
Marcos V. Conde, Zhijun Lei, Wen Li +72
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolutio…
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey
Marcos V. Conde, Florin-Alexandru Vasluianu, Radu Timofte +32
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in…
AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and Results
Marcos V. Conde, Saman Zadtootaghaj, Nabajeet Barman +33
This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge, focused on User-Generated Content (UGC). The aim of this challenge is to gather deep learning-based method…
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…
Event-Based Eye Tracking. AIS 2024 Challenge Survey
Zuowen Wang, Chang Gao, Zongwei Wu +36
This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting t…
Deep Portrait Quality Assessment. A NTIRE 2024 Challenge Survey
Nicolas Chahine, Marcos V. Conde, Daniela Carfora +4
This paper reviews the NTIRE 2024 Portrait Quality Assessment Challenge, highlighting the proposed solutions and results. This challenge aims to obtain an efficient deep neural net…
Simple Image Signal Processing using Global Context Guidance
Omar Elezabi, Marcos V. Conde, Radu Timofte
In modern smartphone cameras, the Image Signal Processor (ISP) is the core element that converts the RAW readings from the sensor into perceptually pleasant RGB images for the end…
InstructIR: High-Quality Image Restoration Following Human Instructions
Marcos V. Conde, Gregor Geigle, Radu Timofte
Image restoration is a fundamental problem that involves recovering a high-quality clean image from its degraded observation. All-In-One image restoration models can effectively re…
BSRAW: Improving Blind RAW Image Super-Resolution
Marcos V. Conde, Florin Vasluianu, Radu Timofte
In smartphones and compact cameras, the Image Signal Processor (ISP) transforms the RAW sensor image into a human-readable sRGB image. Most popular super-resolution methods depart…
Efficient Baselines for Motion Prediction in Autonomous Driving
Carlos Gómez-Huélamo, Marcos V. Conde, Rafael Barea +2
Motion Prediction (MP) of multiple surroundings agents is a crucial task in arbitrarily complex environments, from simple robots to Autonomous Driving Stacks (ADS). Current techniq…
H2O Open Ecosystem for State-of-the-art Large Language Models
Arno Candel, Jon McKinney, Philipp Singer +4
Large Language Models (LLMs) represent a revolution in AI. However, they also pose many significant risks, such as the presence of biased, private, copyrighted or harmful text. For…