← Authors

Michael Maire

29 papers · 2013–2025 · 8 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌈 Renaissance Researcher (8) πŸƒ Academic Marathon (12) 🐝 Cross-Pollinator (10) πŸ—ΊοΈ Taxonomy Completionist (56) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (142) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (29) πŸ”₯ Unstoppable (11) ⚑ Prolific Year (5)

Conferences

CVPR (11) NIPS (7) ICCV (3) ICML (3) ICLR (2) ECCV (1) OSDI (1) WACV (1)

Top co-authors

Pedro Savarese (7) Xin Yuan (5) Xiao Zhang (5) Stella X. Yu (5) Sudarshan Babu (3) Takuya Narihira (3) Greg Shakhnarovich (3) Henry Hoffmann (2) Tri Huynh (2) Gregory Shakhnarovich (2)

Keywords

semantic segmentation (6) convolutional neural network (4) self-supervised learning (4) contrastive learning (3) image segmentation (3) image classification (3) visual representation (3) deep neural network (2) diffusion model (2) affinity matrix (2) unsupervised segmentation (2) stochastic gradient descent (2) visual representation learning (2) image generation (2) transfer learning (2) representation learning (2) instance segmentation (2) attention mechanism (2) learning rate adaptation (2) intrinsic image decomposition (2)

Papers

Nested Diffusion Models Using Hierarchical Latent Priors CVPR 2025
PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement ICCV 2025
Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations CVPR 2024
Latent Intrinsics Emerge from Training to Relight NIPS 2024
ChameleonAPI: Automatic and Efficient Customization of Neural Networks for ML Applications OSDI 2024
HyperFields: Towards Zero-Shot Generation of NeRFs from Text ICML 2024
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation NIPS 2024
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation NIPS 2023
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise NIPS 2022
Boosting Contrastive Self-Supervised Learning With False Negative Cancellation WACV 2022
Multimodal Contrastive Training for Visual Representation Learning CVPR 2021
Online Meta-Learning via Learning with Layer-Distributed Memory NIPS 2021
Information-Theoretic Segmentation by Inpainting Error Maximization CVPR 2021
Domain-Independent Dominance of Adaptive Methods CVPR 2021
Growing Efficient Deep Networks by Structured Continuous Sparsification ICLR 2021
Self-Supervised Visual Representation Learning from Hierarchical Grouping NIPS 2020
Winning the Lottery with Continuous Sparsification NIPS 2020
Pixel Consensus Voting for Panoptic Segmentation CVPR 2020
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks ICML 2020
Multigrid Neural Memory ICML 2020
Learning Implicitly Recurrent CNNs Through Parameter Sharing ICLR 2019
Regularizing Deep Networks by Modeling and Predicting Label Structure CVPR 2018
Sparsely Aggregated Convolutional Networks ECCV 2018
Multigrid Neural Architectures CVPR 2017
Colorization as a Proxy Task for Visual Understanding CVPR 2017
Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding CVPR 2016
Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression ICCV 2015
Learning Lightness From Human Judgement on Relative Reflectance CVPR 2015
Progressive Multigrid Eigensolvers for Multiscale Spectral Segmentation ICCV 2013