Rob Fergus — all works
- Intriguing properties of neural networksarXiv:1312.6199Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, et al.2013 · 5,999 citations
- Object class recognition by unsupervised scale-invariant learning ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetRob Fergus, Pietro Perona, Andrew Zisserman2,029 citations
- Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks ↗arXiv (Cornell University) · no summary yetEmily Denton et al.2015 · 1,626 citations
- OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks ↗arXiv:1312.6229 · no summary yetPierre Sermanet et al.2013 · 1,423 citations
- Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation ↗arXiv (Cornell University) · no summary yetEmily Denton et al.2014 · 1,388 citations
- Visualizing and Understanding Convolutional NetworksarXiv:1311.2901Matthew D Zeiler, Rob Fergus2013 · 771 citations
- Learning object categories from Google's image search ↗no summary yetRob Fergus et al.2005 · 711 citations
- Learning invariant features through topographic filter maps ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetKoray Kavukcuoglu et al.2009 · 281 citations
- A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetRob Fergus, Pietro Perona, Andrew Zisserman2005 · 266 citations
- A Visual Category Filter for Google Images ↗Lecture notes in computer science · no summary yetRobert Fergus, Pietro Perona, Andrew Zisserman2004 · 259 citations
- Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
- Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition ↗International Journal of Computer Vision · no summary yetRob Fergus, Pietro Perona, Andrew Zisserman2006 · 199 citations
- Learning Object Categories From Internet Image Searches ↗Proceedings of the IEEE · no summary yetRob Fergus et al.2010 · 87 citations
- Web scale photo hash clustering on a single machine ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYunchao Gong et al.2015 · 84 citations
- Learning by Asking Questions ↗arXiv:1712.01238 · no summary yetIshan Misra et al.2017 · 75 citations
- Deep neural networks predict category typicality ratings for images ↗no summary yetBrenden M. Lake et al.2015 · 57 citations
- MazeBase: A Sandbox for Learning from Games ↗arXiv (Cornell University) · no summary yetSainbayar Sukhbaatar et al.2015 · 49 citations
- Finding Generalizable Evidence by Learning to Convince Q&A ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Siddharth Karamcheti, Rob Fergus, et al.2019 · 43 citations
- Learning to Discover Efficient Mathematical Identities ↗arXiv (Cornell University) · no summary yetWojciech Zaremba, Karol Kurach, Rob Fergus2014 · 42 citations
- Learning Simple Algorithms from Examples ↗arXiv (Cornell University) · no summary yetWojciech Zaremba et al.2015 · 41 citations
- Collaborating with language models for embodied reasoning ↗arXiv:2302.00763 · no summary yetIshita Dasgupta et al.2023 · 36 citations
- A Sparse Object Category Model for Efficient Learning and Complete Recognition ↗Lecture notes in computer science · no summary yetRob Fergus, Pietro Perona, Andrew Zisserman2006 · 35 citations
- Cambrian-S: Towards Spatial Supersensing in Video ↗arXiv (Cornell University) · no summary yetShusheng Yang et al.2025 · 11 citations
- Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders ↗arXiv (Cornell University) · no summary yetShengbang Tong et al.2026 · 9 citations
- Distilling Internet-Scale Vision-Language Models into Embodied Agents ↗arXiv:2301.12507 · no summary yetTheodore Sumers et al.2023 · 9 citations
- Beyond Language Modeling: An Exploration of Multimodal Pretraining ↗arXiv (Cornell University) · no summary yetShengbang Tong et al.2026 · 6 citations
- SIMS-V: Simulated Instruction-Tuning for Spatial Video Understanding ↗arXiv (Cornell University) · no summary yetEllis Brown et al.2025 · 6 citations
- Benchmark Designers Should "Train on the Test Set" to Expose Exploitable Non-Visual Shortcuts ↗arXiv (Cornell University) · no summary yetEllis Brown et al.2025 · 5 citations
- Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning ↗arXiv (Cornell University) · no summary yetParas Dahal et al.2026
- PaintBench: Deterministic Evaluation of Precise Visual Editing ↗arXiv (Cornell University) · no summary yetXu, Kai et al.2026
- GitSwarm: Decentralized Compounding Inference ↗arXiv (Cornell University) · no summary yetVedant Shah et al.2026
- Exploiting linear structure within convolutional networks for efficient evaluation,” arXiv:1404.0736 ↗no summary yetEmily Denton et al.2014
- Learning Object Categories From Internet Image Searches This paper shows how the results returned by an image search engine can be used to construct models from Internet images and use them for object recognition. ↗no summary yetRob Fergus, Pietro Perona, Andrew Zisserman2010
- A Sparse Object Category Model for Efficient Learning \nand Exhaustive Recognition ↗CaltechAUTHORS (California Institute of Technology) · no summary yetRobert Fergus, Pietro Perona, Andrew Zisserman2005
This page in Markdown → https://md.research.elamur.ai/free/en/authors/rob-fergus/works/