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Hieu Le (Minh Hiếu Lê) |
I am a postdoc at CVLab EPFL working with Prof. Pascal Fua and Mathieu Salzmann. Before that, I obtained my Ph.D. in computer science from Stony Brook Univeristy working with Prof. Dimitris Samaras and spent two years as an applied scientist at Amazon Robotics - Boston.
[2025] A paper on personalized scanpath prediction has been accepted to CVPR 2025.
[2025] A paper on identifying reliable seeds for diffusion models has been accepted to ICLR 2025 as a Spotlight paper.
[2024] Two papers accepted to WACV 2025: Material-Consistent Shadow Edges, and Multi-Class Object Counting.
[2024] Pseudo-Density has been accepted to TMLR. Similar to Latent Density Score, this paper reveals the learning mechanism of generative models.
[2024] Four papers accepted to ECCV 2024: Latent Density Score, Neural Surface Localization, Pseudo-Pixel Weighting, and Beyond Pixels.
[2024] A paper on 3D heart generation has been accepted to MICCAI 2024.
[2024] Our paper on uncertainty estimation has been accepted to ICML 2024.
[2024] Zigzag has been accepted by TMLR. Zigzag is a universal uncertainty estimation method that requires only two inference passes.
[2023] Two papers accepted to CVPR 2023: Zero-Shot Object Counting and Few-Shot Object Detection.
[2023] Selected as an outstanding reviewer at ACCV 2022.
[2022] Our paper on Few-Shot Classification via Generating Representative Prototypes has been accepted to CVPR 2022.
[2022] Our journal paper on Physics-Based Shadow Removal has been accepted by TPAMI 2022.
[2022] Our journal paper on detecting penguin colonies from satellite images has been accepted by Remote Sensing 2022.
[2021] Our paper on Few-Shot Classification has been accepted to ICCV 2021.
[2021] Outstanding Reviewer - CVPR 2021.
[2020] Ph.D. completed.
[2020] Outstanding Reviewer - ECCV 2020.
[2020] Our paper on Weakly-Supervised Shadow Removal has been accepted to ECCV 2020. Project Page.
[2019] Our paper on Shadow Removal has been accepted to ICCV 2019. Project Page.
[2019] Our paper on Semi-Supervised Segmentation has been accepted to CVPR 2019 - CV4GC.
[2019] Our paper on Policy Mining Using Neural Networks has been accepted to SACMAT 2019.
[2018] Two papers accepted to ECCV 2018: ADNet for shadow detection and Iterative Crowd Counting.
[2017] Our paper on Object Co-Localization has been accepted to ICCV 2017, Workshop on CEFRL, Venice, Italy.
[2017] Our poster on Object Co-Localization was presented at VSS 2017 (Florida, US). [Poster]
[2016] Geodesic Features for Video Segmentation has been accepted to ACCV 2016.
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Few-shot Personalized Scanpath Prediction |
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Enhancing Compositional Text-to-Image Generation with Reliable Random Seeds |
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Learning to Count from Pseudo-Labeled Segmentation |
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Shadow Removal Refinement via Material-Consistent Shadow Edges |
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Assessing Sample Quality via the Latent Space of Generative Models |
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Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density |
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Neural Surface Localization for Unsigned Distance Fields |
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Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentation |
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Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifier |
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Generating Anatomically Accurate Heart Structures via Neural Implicit Fields |
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Enabling Uncertainty Estimation in Iterative Neural Networks |
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Zigzag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference |
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Zero-Shot Object Counting |
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Generating Features With Increased Crop-related Diversity For Few-shot Object Detection |
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Generating Representative Samples for Few-Shot Classification |
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Physics-based Shadow Image Decomposition for Shadow Removal |
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A convolutional neural network architecture designed for the automated survey of seabird colonies |
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Variational Feature Disentangling for Fine-Grained Few-Shot Classification |
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Aerial-trained deep learning networks for surveying cetaceans from satellite imagery |
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From Shadow Segmentation to Shadow Removal |
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Shadow Removal via Shadow Image Decomposition |
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Weakly Labeling the Antarctic: The Penguin Colony Case |
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A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation. |
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Iterative Crowd Counting. |
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Co-localization with Category-Consistent CNN Features and Geodesic Distance Propagation |
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Geodesic Distance Histogram Feature for Video Segmentation |
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Efficient video segmentation using parametric graph partitioning |
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Learning Frame-Wise Emotion Intensity for Audio-Driven Talking-Head Generation
Jingyi Xu, Hieu Le, Zhixin Shu, Yang Wang, Yi-Hsuan Tsai,
Dimitris Samaras, 2025 |
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Instance-Aware Generalized Referring Expression Segmentation
E-Ro Nguyen, Hieu Le, Dimitris Samaras, Michael Ryoo, 2025
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Importance-based Token Merging for Diffusion Models
Haoyu Wu, Jingyi Xu, Hieu Le, Dimitris Samaras,
2025 |
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QT-DoG: Quantization-Aware Training for Domain Generalization
Saqib Javed, Hieu Le, Mathieu Salzmann, 2025 |
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Counting Stacked Objects from Multi-View Images
Corentin Dumery, Noa Etté, Jingyi Xu, Aoxiang Fan, Ren Li, Hieu Le, Pascal Fua, 2025 |
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MedTet: An Online Motion Model for 4D Heart Reconstruction
Yihong Chen, Jiancheng Yang, Deniz Sayin Mercadier, Hieu Le, Pascal Fua, 2025 |