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2020 – today
- 2024
[c50]Thomas Serre, Mathieu Fontaine, Éric Benhaim, Geoffroy Dutour, Slim Essid:
A Lightweight Dual-Stage Framework for Personalized Speech Enhancement Based on Deepfilternet2. ICASSP Workshops 2024: 780-784- [c49]Sabine Muzellec, Thomas Fel, Victor Boutin, Léo Andéol, Rufin VanRullen, Thomas Serre:
Saliency strikes back: How filtering out high frequencies improves white-box explanations. ICML 2024 - [i49]Thomas Serre, Mathieu Fontaine, Éric Benhaim, Geoffroy Dutour, Slim Essid:
A lightweight dual-stage framework for personalized speech enhancement based on DeepFilterNet2. CoRR abs/2404.08022 (2024) - [i48]Drew Linsley, Peisen Zhou, Alekh Karkada Ashok, Akash Nagaraj, Gaurav Gaonkar, Francis E. Lewis, Zygmunt Pizlo, Thomas Serre:
The 3D-PC: a benchmark for visual perspective taking in humans and machines. CoRR abs/2406.04138 (2024) - [i47]Victor Boutin, Rishav Mukherji, Aditya Agrawal, Sabine Muzellec, Thomas Fel, Thomas Serre, Rufin VanRullen:
Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks. CoRR abs/2406.06079 (2024) - [i46]Michael A. Lepori, Alexa R. Tartaglini, Wai Keen Vong, Thomas Serre, Brenden M. Lake, Ellie Pavlick:
Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects. CoRR abs/2406.15955 (2024) - [i45]Thomas Fel, Louis Béthune, Andrew Kyle Lampinen, Thomas Serre, Katherine L. Hermann:
Understanding Visual Feature Reliance through the Lens of Complexity. CoRR abs/2407.06076 (2024) - [i44]Sabine Muzellec, Drew Linsley, Alekh Karkada Ashok, Ennio Mingolla, Girik Malik, Rufin VanRullen, Thomas Serre:
Tracking objects that change in appearance with phase synchrony. CoRR abs/2410.02094 (2024) - 2023
- [c48]Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre:
CRAFT: Concept Recursive Activation FacTorization for Explainability. CVPR 2023: 2711-2721 - [c47]Thomas Fel, Melanie Ducoffe, David Vigouroux, Rémi Cadène, Mikael Capelle, Claire Nicodème, Thomas Serre:
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. CVPR 2023: 16153-16163 - [c46]Mohit Vaishnav, Thomas Serre:
GAMR: A Guided Attention Model for (visual) Reasoning. ICLR 2023 - [c45]Victor Boutin, Thomas Fel, Lakshya Singhal, Rishav Mukherji, Akash Nagaraj, Julien Colin
, Thomas Serre:
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines? ICML 2023: 2953-3002 - [c44]Mathieu Chalvidal, Thomas Serre, Rufin VanRullen:
Learning Functional Transduction. NeurIPS 2023 - [c43]Thomas Fel, Victor Boutin, Louis Béthune, Rémi Cadène, Mazda Moayeri, Léo Andéol, Mathieu Chalvidal, Thomas Serre:
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. NeurIPS 2023 - [c42]Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Lore Goetschalckx, Laurent Gardes, Thomas Serre:
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization. NeurIPS 2023 - [c41]Lore Goetschalckx, Lakshmi Narasimhan Govindarajan, Alekh Karkada Ashok, Aarit Ahuja, David L. Sheinberg, Thomas Serre:
Computing a human-like reaction time metric from stable recurrent vision models. NeurIPS 2023 - [c40]Michael A. Lepori, Thomas Serre, Ellie Pavlick:
Break It Down: Evidence for Structural Compositionality in Neural Networks. NeurIPS 2023 - [c39]Drew Linsley, Ivan F. Rodriguez Rodriguez, Thomas Fel, Michael Arcaro, Saloni Sharma, Margaret S. Livingstone, Thomas Serre:
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex. NeurIPS 2023 - [i43]Michael A. Lepori, Thomas Serre, Ellie Pavlick:
Break It Down: Evidence for Structural Compositionality in Neural Networks. CoRR abs/2301.10884 (2023) - [i42]Victor Boutin, Thomas Fel, Lakshya Singhal, Rishav Mukherji, Akash Nagaraj, Julien Colin, Thomas Serre:
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines? CoRR abs/2301.11722 (2023) - [i41]Mathieu Chalvidal, Thomas Serre, Rufin VanRullen:
Learning Functional Transduction. CoRR abs/2302.00328 (2023) - [i40]Drew Linsley, Pinyuan Feng, Thibaut Boissin, Alekh Karkada Ashok, Thomas Fel, Stephanie Olaiya, Thomas Serre:
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception. CoRR abs/2306.03229 (2023) - [i39]Drew Linsley, Ivan Felipe Rodríguez, Thomas Fel, Michael Arcaro, Saloni Sharma, Margaret S. Livingstone, Thomas Serre:
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex. CoRR abs/2306.03779 (2023) - [i38]Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Martin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Laurent Gardes, Thomas Serre:
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. CoRR abs/2306.06805 (2023) - [i37]Thomas Fel, Victor Boutin, Mazda Moayeri, Rémi Cadène, Louis Béthune, Léo Andéol, Mathieu Chalvidal, Thomas Serre:
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. CoRR abs/2306.07304 (2023) - [i36]Lore Goetschalckx, Lakshmi Narasimhan Govindarajan, Alekh Karkada Ashok, Aarit Ahuja, David L. Sheinberg, Thomas Serre:
Computing a human-like reaction time metric from stable recurrent vision models. CoRR abs/2306.11582 (2023) - [i35]Sabine Muzellec, Léo Andéol, Thomas Fel, Rufin VanRullen, Thomas Serre:
Gradient strikes back: How filtering out high frequencies improves explanations. CoRR abs/2307.09591 (2023) - [i34]Michael A. Lepori, Ellie Pavlick, Thomas Serre:
NeuroSurgeon: A Toolkit for Subnetwork Analysis. CoRR abs/2309.00244 (2023) - [i33]Lakshmi Narasimhan Govindarajan, Rex G. Liu, Drew Linsley, Alekh Karkada Ashok, Max Reuter, Michael J. Frank, Thomas Serre:
Diagnosing and exploiting the computational demands of videos games for deep reinforcement learning. CoRR abs/2309.13181 (2023) - [i32]Michael A. Lepori, Thomas Serre, Ellie Pavlick:
Uncovering Intermediate Variables in Transformers using Circuit Probing. CoRR abs/2311.04354 (2023) - [i31]Shreyas Sundara Raman, Madeline H. Pelgrim, Daphna Buchsbaum, Thomas Serre:
Categorizing the Visual Environment and Analyzing the Visual Attention of Dogs. CoRR abs/2311.11988 (2023) - [i30]Drew Linsley, Thomas Serre:
Fixing the problems of deep neural networks will require better training data and learning algorithms. CoRR abs/2311.12819 (2023) - 2022
- [j11]Mohit Vaishnav, Rémi Cadène, Andrea Alamia, Drew Linsley, Rufin VanRullen, Thomas Serre:
Understanding the Computational Demands Underlying Visual Reasoning. Neural Comput. 34(5): 1075-1099 (2022) - [c38]Victor Boutin, Lakshya Singhal, Xavier Thomas, Thomas Serre:
Diversity vs. Recognizability: Human-like generalization in one-shot generative models. NeurIPS 2022 - [c37]Mathieu Chalvidal, Thomas Serre, Rufin VanRullen:
Meta-Reinforcement Learning with Self-Modifying Networks. NeurIPS 2022 - [c36]Julien Colin, Thomas Fel, Rémi Cadène, Thomas Serre:
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. NeurIPS 2022 - [c35]Thomas Fel, Ivan F. Rodriguez Rodriguez, Drew Linsley, Thomas Serre:
Harmonizing the object recognition strategies of deep neural networks with humans. NeurIPS 2022 - [c34]Aimen Zerroug, Mohit Vaishnav, Julien Colin, Sebastian Musslick, Thomas Serre:
A Benchmark for Compositional Visual Reasoning. NeurIPS 2022 - [c33]Thomas Fel, David Vigouroux, Rémi Cadène, Thomas Serre:
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks. WACV 2022: 1565-1575 - [c32]Amor Ben Tanfous, Aimen Zerroug, Drew Linsley, Thomas Serre:
How and What to Learn: Taxonomizing Self-Supervised Learning for 3D Action Recognition. WACV 2022: 2888-2897 - [i29]Mathieu Chalvidal, Thomas Serre, Rufin VanRullen:
A Discourse on MetODS: Meta-Optimized Dynamical Synapses for Meta-Reinforcement Learning. CoRR abs/2202.02363 (2022) - [i28]Thomas Fel, Melanie Ducoffe, David Vigouroux, Rémi Cadène, Mikael Capelle, Claire Nicodeme, Thomas Serre:
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. CoRR abs/2202.07728 (2022) - [i27]Victor Boutin, Lakshya Singhal, Xavier Thomas, Thomas Serre:
Diversity vs. Recognizability: Human-like generalization in one-shot generative models. CoRR abs/2205.10370 (2022) - [i26]Thomas Fel, Lucas Hervier, David Vigouroux, Antonin Poché, Justin Plakoo, Rémi Cadène, Mathieu Chalvidal, Julien Colin, Thibaut Boissin, Louis Béthune, Agustin Martin Picard, Claire Nicodeme, Laurent Gardes, Grégory Flandin, Thomas Serre:
Xplique: A Deep Learning Explainability Toolbox. CoRR abs/2206.04394 (2022) - [i25]Mohit Vaishnav, Thomas Serre:
MAREO: Memory- and Attention- based visual REasOning. CoRR abs/2206.04928 (2022) - [i24]Aimen Zerroug, Mohit Vaishnav, Julien Colin, Sebastian Musslick, Thomas Serre:
A Benchmark for Compositional Visual Reasoning. CoRR abs/2206.05379 (2022) - [i23]Mohit Vaishnav, Thomas Fel, Ivan Felipe Rodríguez, Thomas Serre:
Conviformers: Convolutionally guided Vision Transformer. CoRR abs/2208.08900 (2022) - [i22]Thomas Fel, Ivan Felipe Rodríguez, Drew Linsley, Thomas Serre:
Harmonizing the object recognition strategies of deep neural networks with humans. CoRR abs/2211.04533 (2022) - [i21]Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre:
CRAFT: Concept Recursive Activation FacTorization for Explainability. CoRR abs/2211.10154 (2022) - 2021
- [c31]Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen, Thomas Serre:
Go with the flow: Adaptive control for Neural ODEs. ICLR 2021 - [c30]Drew Linsley, Girik Malik, Junkyung Kim, Lakshmi Narasimhan Govindarajan, Ennio Mingolla, Thomas Serre:
Tracking Without Re-recognition in Humans and Machines. NeurIPS 2021: 19473-19486 - [c29]Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre:
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. NeurIPS 2021: 26005-26014 - [i20]Matthew Ricci, Minju Jung, Yuwei Zhang, Mathieu Chalvidal, Aneri Soni, Thomas Serre:
KuraNet: Systems of Coupled Oscillators that Learn to Synchronize. CoRR abs/2105.02838 (2021) - [i19]Drew Linsley, Girik Malik, Junkyung Kim, Lakshmi Narasimhan Govindarajan, Ennio Mingolla, Thomas Serre:
Tracking Without Re-recognition in Humans and Machines. CoRR abs/2105.13351 (2021) - [i18]Mohit Vaishnav, Rémi Cadène, Andrea Alamia, Drew Linsley, Rufin VanRullen, Thomas Serre:
Understanding the computational demands underlying visual reasoning. CoRR abs/2108.03603 (2021) - [i17]Girik Malik, Drew Linsley, Thomas Serre, Ennio Mingolla:
The Challenge of Appearance-Free Object Tracking with Feedforward Neural Networks. CoRR abs/2110.02772 (2021) - [i16]Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre:
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. CoRR abs/2111.04138 (2021) - [i15]Thomas Fel, Julien Colin, Rémi Cadène, Thomas Serre:
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. CoRR abs/2112.04417 (2021) - 2020
- [c28]Junkyung Kim, Drew Linsley, Kalpit Thakkar, Thomas Serre:
Disentangling neural mechanisms for perceptual grouping. ICLR 2020 - [c27]Drew Linsley, Junkyung Kim, Alekh Ashok, Thomas Serre:
Recurrent neural circuits for contour detection. ICLR 2020 - [c26]Drew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan, Rex G. Liu, Thomas Serre:
Stable and expressive recurrent vision models. NeurIPS 2020 - [i14]Drew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan, Rex G. Liu, Thomas Serre:
Stable and expressive recurrent vision models. CoRR abs/2005.11362 (2020) - [i13]Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen, Thomas Serre:
Neural Optimal Control for Representation Learning. CoRR abs/2006.09545 (2020) - [i12]Drew Linsley, Junkyung Kim, Alekh Ashok, Thomas Serre:
Recurrent neural circuits for contour detection. CoRR abs/2010.15314 (2020) - [i11]Victor Boutin, Aimen Zerroug, Minju Jung, Thomas Serre:
Iterative VAE as a predictive brain model for out-of-distribution generalization. CoRR abs/2012.00557 (2020)
2010 – 2019
- 2019
- [c25]Drew Linsley, Dan Shiebler, Sven Eberhardt, Thomas Serre:
Learning what and where to attend. ICLR (Poster) 2019 - [i10]Junkyung Kim, Drew Linsley, Kalpit Thakkar, Thomas Serre:
Disentangling neural mechanisms for perceptual grouping. CoRR abs/1906.01558 (2019) - 2018
- [c24]Drew Linsley, Jeremy W. Linsley, Tarun Sharma, Nathan Meyers, Thomas Serre:
Learning to predict action potentials end-to-end from calcium imaging data. CISS 2018: 1-6 - [c23]Matthew Ricci, Junkyung Kim, Thomas Serre:
Same-different problems strain convolutional neural networks. CogSci 2018 - [c22]Drew Linsley, Junkyung Kim, Vijay Veerabadran, Charles Windolf, Thomas Serre:
Learning long-range spatial dependencies with horizontal gated recurrent units. NeurIPS 2018: 152-164 - [i9]Matthew Ricci, Junkyung Kim, Thomas Serre:
Not-So-CLEVR: Visual Relations Strain Feedforward Neural Networks. CoRR abs/1802.03390 (2018) - [i8]Drew Linsley, Junkyung Kim, Vijay Veerabadran, Thomas Serre:
Learning long-range spatial dependencies with horizontal gated-recurrent units. CoRR abs/1805.08315 (2018) - [i7]Drew Linsley, Dan Scheibler, Sven Eberhardt, Thomas Serre:
Global-and-local attention networks for visual recognition. CoRR abs/1805.08819 (2018) - [i6]Yuliang Guo, Lakshmi Narasimhan Govindarajan, Benjamin B. Kimia, Thomas Serre:
Robust pose tracking with a joint model of appearance and shape. CoRR abs/1806.11011 (2018) - [i5]Drew Linsley, Junkyung Kim, David Berson, Thomas Serre:
Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks. CoRR abs/1811.11356 (2018) - 2017
- [c21]Drew Linsley, Sven Eberhardt, Tarun Sharma, Pankaj Gupta, Thomas Serre:
What are the Visual Features Underlying Human Versus Machine Vision? ICCV Workshops 2017: 2706-2714 - [i4]Drew Linsley, Sven Eberhardt, Tarun Sharma, Pankaj Gupta, Thomas Serre:
Clicktionary: A Web-based Game for Exploring the Atoms of Object Recognition. CoRR abs/1701.02704 (2017) - 2016
- [j10]Maxime Cauchoix, Sébastien M. Crouzet, Denis Fize, Thomas Serre:
Fast ventral stream neural activity enables rapid visual categorization. NeuroImage 125: 280-290 (2016) - [j9]Peter Wilf, Shengping Zhang, Sharat Chikkerur, Stefan A. Little, Scott L. Wing, Thomas Serre:
Computer vision cracks the leaf code. Proc. Natl. Acad. Sci. USA 113(12): 3305-3310 (2016) - [c20]Sven Eberhardt, Jonah G. Cader, Thomas Serre:
How Deep is the Feature Analysis underlying Rapid Visual Categorization? NIPS 2016: 1100-1108 - [c19]Hilde Kuehne, Juergen Gall, Thomas Serre:
An end-to-end generative framework for video segmentation and recognition. WACV 2016: 1-8 - [i3]Sven Eberhardt, Jonah Cader, Thomas Serre:
How Deep is the Feature Analysis underlying Rapid Visual Categorization? CoRR abs/1606.01167 (2016) - 2015
- [j8]Sarah M. Parker, Thomas Serre:
Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties. Frontiers Comput. Neurosci. 9: 115 (2015) - [j7]Imri Sofer, Sébastien M. Crouzet, Thomas Serre:
Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization. PLoS Comput. Biol. 11(9) (2015) - [i2]Hilde Kuehne, Thomas Serre:
Cooking in the kitchen: A generative approach to the recognition, parsing and segmentation of human daily activities. CoRR abs/1508.06073 (2015) - [i1]Hilde Kuehne, Thomas Serre:
Towards a generative approach to activity recognition and segmentation. CoRR abs/1509.01947 (2015) - 2014
- [c18]Hilde Kuehne, Ali Bilgin Arslan, Thomas Serre:
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities. CVPR 2014: 780-787 - [c17]Yanhao Zhang, Shengping Zhang, Qingming Huang, Thomas Serre:
Learning Sparse Prototypes for Crowd Perception via Ensemble Coding Mechanisms. HBU 2014: 86-100 - [c16]David P. Reichert, Thomas Serre:
Neuronal Synchrony in Complex-Valued Deep Networks. ICLR (Poster) 2014 - [r1]Thomas Serre:
Hierarchical Models of the Visual System. Encyclopedia of Computational Neuroscience 2014 - 2013
- [j6]Tomaso A. Poggio, Thomas Serre:
Models of visual cortex. Scholarpedia 8(4): 3516 (2013) - [c15]Cheston Tan, Jedediah M. Singer, Thomas Serre, David L. Sheinberg, Tomaso A. Poggio:
Neural representation of action sequences: how far can a simple snippet-matching model take us? NIPS 2013: 593-601 - 2012
- [c14]Jun Zhang, Youssef Barhomi, Thomas Serre:
A New Biologically Inspired Color Image Descriptor. ECCV (5) 2012: 312-324 - 2011
- [c13]Sharat Chikkerur, Thomas Serre, Cheston Tan, Tomaso A. Poggio:
Attention as a Bayesian inference process. Human Vision and Electronic Imaging 2011: 786511 - [c12]Hildegard Kuehne, Hueihan Jhuang, Estíbaliz Garrote, Tomaso A. Poggio, Thomas Serre:
HMDB: A large video database for human motion recognition. ICCV 2011: 2556-2563 - [c11]Maxime Cauchoix, Ali Bilgin Arslan, Denis Fize, Thomas Serre:
The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques. MLINI 2011: 164-171 - 2010
- [j5]Thomas Serre, Tomaso A. Poggio:
A neuromorphic approach to computer vision. Commun. ACM 53(10): 54-61 (2010) - [j4]Leila Reddy, Naotsugu Tsuchiya, Thomas Serre:
Reading the mind's eye: Decoding category information during mental imagery. NeuroImage 50(2): 818-825 (2010) - [c10]Roi Kliper, Thomas Serre, Daphna Weinshall, Israel Nelken:
The story of a single cell: Peeking into the semantics of spikes. CIP 2010: 281-286 - [c9]Hueihan Jhuang, Estíbaliz Garrote, Nicholas Edelman, Tomaso A. Poggio, Andrew Steele, Thomas Serre:
Trainable, vision-based automated home cage behavioral phenotyping. MB 2010: 33:1-33:4
2000 – 2009
- 2007
- [j3]Bernd Heisele, Thomas Serre, Tomaso A. Poggio:
A Component-based Framework for Face Detection and Identification. Int. J. Comput. Vis. 74(2): 167-181 (2007) - [j2]Thomas Serre, Lior Wolf, Stanley M. Bileschi, Maximilian Riesenhuber, Tomaso A. Poggio:
Robust Object Recognition with Cortex-Like Mechanisms. IEEE Trans. Pattern Anal. Mach. Intell. 29(3): 411-426 (2007) - [c8]Hueihan Jhuang, Thomas Serre, Lior Wolf, Tomaso A. Poggio:
A Biologically Inspired System for Action Recognition. ICCV 2007: 1-8 - 2005
- [c7]Thomas Serre, Lior Wolf, Tomaso A. Poggio:
Object Recognition with Features Inspired by Visual Cortex. CVPR (2) 2005: 994-1000 - [c6]Rodrigo Sigala, Thomas Serre, Tomaso A. Poggio, Martin A. Giese:
Learning Features of Intermediate Complexity for the Recognition of Biological Motion. ICANN (1) 2005: 241-246 - 2004
- [c5]Yuri Ivanov, Bernd Heisele, Thomas Serre:
Using Component Features for Face Recognition. FGR 2004: 421-426 - 2003
- [j1]Bernd Heisele, Thomas Serre, Sam Prentice, Tomaso A. Poggio:
Hierarchical classification and feature reduction for fast face detection with support vector machines. Pattern Recognit. 36(9): 2007-2017 (2003) - 2002
- [c4]Thomas Serre, Maximilian Riesenhuber, Jennifer Louie, Tomaso A. Poggio:
On the Role of Object-Specific Features for Real World Object Recognition in Biological Vision. Biologically Motivated Computer Vision 2002: 387-397 - 2001
- [c3]Bernd Heisele, Thomas Serre, Sayan Mukherjee, Tomaso A. Poggio:
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images. CVPR (2) 2001: 18-24 - [c2]Bernd Heisele, Thomas Serre, Massimiliano Pontil, Tomaso A. Poggio:
Component-based Face Detection. CVPR (1) 2001: 657-662 - [c1]Bernd Heisele, Thomas Serre, Massimiliano Pontil, Thomas Vetter, Tomaso A. Poggio:
Categorization by Learning and Combining Object Parts. NIPS 2001: 1239-1245
Coauthor Index
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