About
Welcome to the homepage of the “European Computer Vision Association (ECVA)”, a non-profit organization domiciled in Zurich. The Association’s mission is the furthering of information dissemination concerning research on the theory and practice of computer vision. It will promote the field and its researchers by the organisation of dedicated activities.
Conferences
ECVA will, inter alia, carry out activities to organise the European Conference on Computer Vision (ECCV) series and support the organisers of the ECCV both scientifically and logistically. Below you will find an overview of some past, current and future ECCV conferences for further information.
ECCV | City | General Chairs | Program Chairs | Website | Papers | 2024 | Milan | L. Leal-Taixe, A, Fitzgibbon, V. Murino | A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, G. Varol | https://eccv2024.ecva.net |
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2022 | Tel Aviv | Rita Cucchiara, Jiri Matas, Amnon Shashua, Lihi Zelnik-Manor | Shai Avidan, Gabriel Brostow, Giovanni Maria Farinella, Tal Hassner | https://eccv2022.ecva.net | ||
2020 | Glasgow, Scotland | Bob Fisher, Emanuele Trucco, Vittorio Ferrari, Cordelia Schmid | Andrea Vedaldi, Jan Michael Frahm, Thomas Brox, Horst Bischof | http://eccv2020.eu | ||
2018 | Munich, Germany | Horst Bischof, Daniel Cremers, Bernt Schiele, Ramin Zabih | Vittorio Ferrari, Martial Hebert, Cristian Sminchisescu, Yair Weiss | https://eccv2018.org | ||
2016 | Amsterdam, Netherlands | Theo Gevers, Arnold Smeulders | Jiri Matas, Bastian Leibe, Max Welling, Nicu Sebe | http://www.eccv2016.org | ||
2014 | Zürich, Switzerland | Luc Van Gool, Marc Pollefeys | Tinne Tuytelaars, Bernt Schiele, Tomas Pajdla, David Fleet | http://eccv2014.org | ||
2012 | Firenze, Italy | Roberto Cipolla, Carlo Colombo, Alberto Del Bimbo | Andrew Fitzgibbon, Svetlana Lazebnik, Yoichi Sato, Cordelia Schmid | https://eccv2012.unifi.it | ||
2010 | Crete, Greece | Antonis Argyros, Panos Trahanias, George Tziritas | Kostas Daniilidis, Petros Maragos, Nikos Paragios | https://www.ics.forth.gr/eccv2010 | ||
2008 | Marseille, France | Jean Ponce | David Forsyth, Philip Torr, Andrew Zisserman | http://eccv2008.inrialpes.fr | ||
2006 | Graz, Austria | Axel Pinz | Horst Bischof, Ales Leonardis | http://eccv2006.tugraz.at | ||
2004 | Prague, Czech Republic | Vaclav Hlavac | Tomas Pajdla, Jiri (George) Matas | http://cmp.felk.cvut.cz/eccv2004/ |
ECCV Awards
Below a comprehensive listing of ECCV awards since 2004.
Best Paper Awards
Jeremy Klotz, Shree NayarMinimalist Vision with Freeform Pixels
Best Paper Awards – Honorable Mention
Vitali Petsiuk, Kate SaenkoConcept Arithmetics for Circumventing Concept Inhibition in Diffusion Models
Stanislav Pidhorskyi, Tomas Simon, Gabriel Schwartz, He Wen, Yaser Sheikh, Jason SaragihRasterized Edge Gradients: Handling Discontinuities Differentially
PAMI Everingham Prize
The CelebA TeamZiwei Liu, Ping Luo, Xiaogang Wang, Xiaoou Tang
for a family of datasets that has accelerated the progress in generative image modeling and many other tasks
David Forsythfor continual advice and wisdom in overseeing the computer vision community's conferences and journals
Koenderink Prize
Jakob Engel, Thomas Schöps, Daniel CremersLSD-SLAM: Large-Scale Direct Monocular SLAM
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence ZitnickMicrosoft COCO: Common Objects in Context
Best Paper Awards
Xingjian Zhen, Zihang Meng, Rudrasis Chakraborty, Vikas SinghOn the Versatile Uses of Partial Distance Correlation in Deep Learning
Best Paper Awards – Honorable Mention
Ishit Mehta, Manmohan Chandraker, Ravi RamamoorthiA Level Set Theory for Neural Implicit Evolution under Explicit Flows
Garvita Tiwari, Dimitrije Antic, Jan E. Lenssen, Nikolaos Sarafianos, Tony Tung, Gerard Pons-MollPose-NDF: Modelling Human Pose Manifolds with Neural Distance Fields
Everingham Prize
Walter J. ScheirerOutstanding long-term service to the computer vision community
Khurram Soomro, Amir Roshan Zamir and Mubarak Shah, Hilde Kuehne, Hueihan Jhuang, Estibaliz Garrote, Tomaso A. Poggio, Thomas SerreThe UCF101 and HMD51 dataset teams
Koenderink Prize
Daniel J. Butler, Jonas Wulff, Garrett B. Stanley, Michael J. BlackA naturalistic open source movie for optical flow evaluation
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, Rob FergusIndoor Segmentation and Support Inference from RGBD Images
Best Demo
Yair Moshe, Dan-Ilan Ben-David, Eran Mann, Sagie Baboach, Iddo Bar-Haim, Shoval Gerbi, Adam Katav, Technion – Israel Institute of Technology, IsraelUsing a Smartphone for Augmented Reality in a Classroom
Best Paper Awards
Zachary Teed, Jia DengRAFT: Recurrent All-Pairs Field Transforms for Optical Flow
Best Paper Awards – Honorable Mention
Mengtian Li, Yu-Xiong Wang, Deva RamananTowards Streaming Perception
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, Ren NgNeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Everingham Prize
Antonio TorralbaMultiple Datasets
Johannes SchönbergerCOLMAP SFM and MVS software library
Koenderink Prize
Florent Perronnin, Jorge Sánchez and Thomas MensinkImproving the Fisher Kernel for Large-Scale Image Classification
Michael Calonder, Vincent Lepetit, Christoph Strecha, and Pascal FuaBrief: Binary robust independent elementary features
Best Demo
Rita Cucchiara, Matteo Fabbri, and Simone Calderara, University of Modena and Reggio Emilia, ItalyInter-Homines
Best Paper Awards
Martin Sundermeyer, Zoltan Marton, Maximilian Durner, Manuel Brucker, Rudolph TriebelImplicit 3D Orientation Learning for 6D Object Detection from RGB Images
Best Paper Awards – Honorable Mention
Yuxin Wu, Kaiming HeGroup Normalization
Albert Pumarola, Antonio Agudo, Aleix M. Martinez, Alberto Sanfeliu, Francesco Moreno-NoguerGANimation: Anatomically-aware Facial Animation from a Single Image
Everingham Prize
Alan Smeaton, Wessel Kraaij, Paul Over, George AwadFor a series of datasets and workshops since 2003 that have driven progress in large scale Video Retrieval.
Changchang WuFor providing a well documented software library for Structure from Motion that has been used effortlessly by so many.
Koenderink Prize
Herve Jegou, Matthijs Douze, Cordelia SchmidHamming Embedding and Weak Geometric Consistency for Large Scale Image Search
Helmut Grabner, Christian Leistner, Horst BischofSemi-supervised On-Line Boosting for Robust Tracking
Best Paper Awards
Hanme Kim, Stefan Leutenegger, and Andrew J. DavisonReal-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera
Best Paper Awards – Honorable Mention
Jonathan Barron and Ben PooleThe Fast Bilateral Solver
Everingham Prize
Alex Berg, Jia Deng, Fei-Fei Li, Wei, Liu, Olga Russakovsky and team – ImageNetFor a series of datasets and challenges since 2010 that have had such impact on the computer vision field. ImageNet built on the Caltech101/256 datasets, increasing the number of images by orders of magnitude and enabling the development of new algorithms.
Ramin ZabihFor extensive, generous, service to the community: As long-term head of the IEEE PAMI Technical Committee he introduced many reforms, including to the awards process and the relationship to the IEEE. And he has been the driving force in creating and running the Computer Vision Foundation (CVF).
Koenderink Prize
Herbert Bay, Tinne Tuytelaars, and Luc Van GoolSurf: Speeded up robust features (ECCV 2006)
Edward Rosten and Tom DrummondMachine learning for high-speed corner detection (ECCV 2006)
Best Student Paper Award
Emma Alexander, Qi Guo, Sanjeev Koppal, Steven Gortler, and Todd ZicklerFocal Flow: Measuring Distance and Velocity with Defocus and Differential Motion
Best Paper Awards
Kevin Matzen and Noah SnavelyScene Chronology
Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig AdamLarge-Scale Object Classification using Label Relation Graphs
Best Paper Awards – Honorable Mention
Matt Zeiler and Rob FergusVisualizing and Understanding Convolutional Neural Networks
PAMI Everingham Prize
Terry and Ginger BoultFor extensive, generous, long-term service to the community in the management of computer vision conferences and workshops.
Koenderink Prize
Thomas Brox, Andrès Bruhn, Nils Papenberg & Joachim Weickert (ECCV 2004)High Accuracy Optical Flow Estimation Based on a Theory for Warping
Timo Ahonen, Abdenour Hadid & Matti Pietikäinen (ECCV 2004)Face Recognition with Local Binary Patterns
Best Paper Award
Daniel Kuettel, Matthieu Guillaumin and Vittorio FerrariSegmentation Propagation in ImageNet
Best Paper Award – Honorable Mention
Kris Kitani, Brian D. Ziebart, James Bagnell and Martial HebertActivity Forecasting
Koenderink Prize
Vladimir Kolmogorov and Ramin ZabihWhat Energy Functions Can Be Minimized via Graph Cuts?
Best Student Paper Award
Jianxiong Xiao and Yasutaka FurukawaReconstructing the World’s Museums
Best Paper Award
L. Laticky, C. Russell, P. Kohli and P.H.S. TorrGraph Cut based Inference with Co-occurrence Statistics
Runner-Up Paper Award
A. Gupta, A. Efros and M. HebertBlocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics
Koenderink Prize
H. Sidenbladh, M.J. Black and D.J. FleetStochastic Tracking of 3D Human Figures Using 2D Image Motion (ECCV 2000)
M. Weber, M. Welling and P. PeronaFor the ECCV’2000 paper entitled: Unsupervised Learning of Models for Recognition
Best Student Paper Award
T. Pätz and T. PreusserAmbrosio-Tortorelli Segmentation of Stochastic Images
Best Paper Award
Geremy Heitz and Daphne KollerLearning Spatial Context: Using Stuff to Find Things
Koenderink Prize
Michael Isard and Andrew BlakeContour Tracking by Stochastic Propagation of Conditional Density (ECCV 1996)
Olivier Faugeras, Quang-Tuan Luong, and Steve MaybankCamera self-calibration: theory and experiments (ECCV 1992)
Best Student Paper Award
Matthew B. Blaschko and Christoph H. LampertLearning to Localize Objects with Structured Output Regression
Longuet-Higgins Best Paper Award
Anat Levin, Yair WeissLearning to Combine Bottom-up and Top-down Segmentation
Best Paper Award – Honorable Mention
Samuel W. Hasinoff, Kiriakos N. KutulakosConfocal Stereo
Omar Ait-Aider, Nicolas Andreff, Jean Marc Lavest, and Philippe MartinetSimultaneous Object Pose and Velocity Computation Using a Single View from a Rolling Shutter Camera
Longuet-Higgins Best Paper Award
T. Brox, A. Bruhn, N. Papenberg, and J. WeickertHigh Accuracy Optical Flow Estimation Based on a Theory for Warping
Best Paper Award – Honorable Mention
René Vidal and Yi MaA Unified Algebraic Approach to 2-D and 3-D Motion Segmentation
Best Paper – Cognitive Vision
Kenji Okuma, Ali Taleghani, Nando de Freitas, James J. Little, and David G. LoweA Boosted Particle Filter: Multitarget Detection and Tracking
ECVA Young Researcher Award
With the Young Researcher Award, ECVA recognizes and encourages outstanding research achievements of young researchers in computer vision. Each awardee will receive Euro 5000 prize money. There will be one award every year, which will be awarded at the next ECCV conference.
Deadline
The deadline for nominating a candidate for the years 2024 and 2025 is:April 30, 2026 (End of Day, Anywhere on Earth)
Eligibility
Young researchers must be based at a European research institution and should not be older than 35. Their main scope of research should be in computer vision or be strongly linked to computer vision.
Selection Criteria
Nominations will be reviewed by a selection committee for the quality and significance of the research contributions of the young researcher. Emphasis will be on the research after their PhD.
How to Nominate
The nomination (self-nominations are not allowed) must include:- A short summary (approx. 2 pages) of the main research achievements
- 3-5 of the most important publications
- A scan of the dissertation certificate (which includes the date of the defense)
- The candidate’s CV
- A short laudation (40-80 words)
Please use this template (pdf) (latex) to nominate a candidate and send the nomination (preferably as a single pdf file) to yr-award@ecva.net If you should have any questions, please send an email to yr-award@ecva.net.
Angela Dai
Angela stands out as a pioneering researcher in 3D scene reconstruction and semantic scene understanding. Angela’s research has played a pivotal role in establishing modern 3D deep learning as a prominent and influential area of study. Her efforts have significantly broadened the scope of visual perception, transforming the landscape of research in the digitization and understanding of 3D environments.
Johannes Schönberger
Johannes Schönberger has made numerous significant contributions to geometric computer vision and, through his dedication to open and reproducible research, has enabled a large body of work in both academia and industry. Since earning his PhD, he has advanced and influenced the state of the art in topics related to mapping and localization as well as pioneered new research directions in the area of privacy preserving methods.
Zeynep Akata
Zeynep Akata has had a number of significant contributions in multimodal deep learning, in vision and language for low-shot learning and in explainable machine learning. Her research defined the state of the art for zero-shot learning and her natural language explanations provided novel human-understandable justifications both for fine-grained visual classification and autonomous driving. She is a full professor at Tubingen University and leads a research group there. She has received a number of awards.
Amir Zamir
With a remarkable combination of creativity, productivity, and technical depth, Amir Zamir stands out as an emerging superstar in computer vision. Since earning his PhD, Prof. Zamir has pioneered highly influential approaches in multi-task/transfer learning and 3D environment simulation that serve as inspiration not simply for follow-up papers, but for entire research groups – both in academia and in industry. His work points the way forward as our field transitions from the era of “dataset AI” to the embodied AI future.
ECVA PhD Award
With the ECVA PhD Award, ECVA recognizes and encourages outstanding research achievements during the dissertation phase, in the field of computer vision. Each awardee will receive Euro 2500 prize money. There will be two awards every year, which will be awarded at the next ECCV conference.
Deadline
The deadline for nominating a dissertation for the years 2024 and 2025 is:April 30, 2026 (End of Day, Anywhere on Earth)
Eligibility
Any European dissertation in the area of computer vision that has been defended in 2024 / 2025 can be nominated. A dissertation is considered European if the dissertation has been performed primarily at a European research institution.
Selection Criteria
Dissertations will be reviewed for technical depth and significance of the research contribution and potential impact on theory and practice.
How to Nominate
The nomination (self-nominations by the author of the dissertation are not allowed) must include:- A short summary (approx. 2 pages) of the main research achievements of the dissertation
- 2-3 of the most important publications
- A scan of the dissertation certificate (which includes the date of the defense)
- Final version of the dissertation as pdf (or link to pdf)
- The candidate’s CV
- A short laudation (40-80 words)
Please use this template (pdf) (latex) to nominate a candidate and send the nomination (preferably as a single pdf file) to phd-award@ecva.net. If you should have any questions, please send an email to phd-award@ecva.net.
Yaoyao Liu
Learning from Imperfect Data: Incremental Learning and Few-shot LearningYaoyao Liu introduced many creative methods to apply the “learning-to-learn” idea in few-shot learning, continual learning, and their applications. In terms of algorithmic development, his work leveraged online learning, reinforcement learning, bilevel optimization to make a various of prefixed components learnable and adaptive. In terms of applications, his work explored many important real-world tasks, including object detection and medical imaging. His scientific works have become highly influential in the field.
Songyou Peng
Neural Scene Representations for 3D Reconstruction and Scene UnderstandingDr. Peng has significantly advanced the field of 3D computer vision, focusing on the areas of 3D reconstruction and 3D scene understanding. His research in his PhD thesis not only addresses the challenges of large-scale 3D scene reconstruction but also pioneers the use of large vision foundation models for zero-shot 3D scene understanding. His works have inspired extensive follow-up research across various fields of computer vision, robotics, and graphics.
Jan Eric Lenssen
Differentiable Algorithms with Data-driven Parameterization in 3D VisionIn his PhD work, Jan Eric Lenssen made a large number of very original, technically deep, and significant contributions in the area of geometric deep learning, graph neural networks, and 3D representation learning. His contributions to efficient GPU message passing algorithms laid the foundation for Pytorch Geometric, the most used graph neural network library world-wide and for the successful startup Kumo.ai.
Shangzhe Wu
Unsupervised Learning of 3D Objects in the WildShangzhe Wu’s PhD pioneers monocular 3D reconstruction of deformable objects without 3D supervision from images and videos collected in the wild. The thesis advances this field on two fronts simultaneously: (1) demonstrating an unprecedented quality of results and (2) using only minimal assumptions, leading to both significant practical values and scientific insights. The work in this thesis has inspired a wide range of follow-up work by the community and has significantly shaped the field of unsupervised 3D learning.
Iro Laina
Semantics, Language and Geometry: Learning to Understand the SceneIro Laina’s dissertation addresses a broad range of challenging problems in computer vision, and specifically in scene understanding. The dissertation makes a series of timely, strong, and innovative scientific contributions by breaking down the overarching scene understanding problem to geometric, semantic, and linguistic components. It advances the state of the art in perceptual tasks and in the intersection of vision and language. The content of the thesis has been adopted in widespread real-world applications and has created significant impact.
Yongqin Xian
Learning from Limited Labeled Data – Zero Shot and Few-Shot LearningYongqin Xian made significant contributions in the area of zero-shot and few-shot learning. He proposed novel feature generating frameworks that have defined the state of the art in this area. He introduced the first approach for zero-label semantic segmentation and pushed the boundary of few-shot video classification by leveraging unlabeled videos from a large dataset. In addition, his zero-shot learning benchmark has become highly influential in the field.
Marcella Cornia
Learning to Describe Salient Objects in Images with Vision and LanguageMarcella Cornia is a cocktail of excellent technical expertise and great intellectual curiosity; the cherry on the glass is her kindness and willingness to work in both pure research projects, industrial research, and public engagement.
Triantafyllos Afouras
Audio-visual Deep LearningTriantafyllos Afouras’ outstanding dissertation introduces multiple creative ways to use audio and visual data in machine learning and in applications. It explores cross-modal and self-supervised learning for the important areas of lip reading, audio-visual speaker separation and enhancement, audio-visual object detection, and sign language recognition. Both the scientific outcomes of the dissertation and the datasets released have had a high impact in terms of citations and downloads.
Board
The Executive Board of the Computer Vision Association
President
Daniel Cremers
Vice President
Tinne Tuytelaars
Treasurer
Tomas Pajdla