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.
News
[2025] Two papers have been accepted to ICCV 2025.
[2025] Pair-wise implicit constraint has been early accepted (top 9%) to MICCAI 2025.
[2025] Qt-DoG 🐶 has been accepted to ICML 2025.
[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.
[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.
Publications
Importance-based Token Merging for Efficient Image and Video Generation
Haoyu Wu, Jingyi Xu, Hieu Le, Dimitris Samaras,
2025
International Conference on Computer Vision (ICCV), 2025. [Preprint][Project Page]
TL;DR: A novel token-merging method speeds up diffusion models by preserving important tokens,
enhancing sample quality with minimal computational cost.
Counting Stacked Objects
Corentin Dumery, Noa Ette, Aoxiang Fan, Ren Li, Jingyi Xu, Hieu Le, Pascal Fua
International Conference on Computer Vision (ICCV), 2025. [Preprint]
TL;DR: We do 3D volume reconstruction from multi-view images to count hidden objects
Pairwise-Constrained Implicit Functions for 3D Human Heart Modeling
Hieu Le, Jingyi Xu, Nicolas Talabot, Jiancheng Yang, Pascal Fua. 2025
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025. [Preprint]
We use monte a carlo sampling method for finding relevant points to refine pairs of SDF surfaces, making them contact each other without penetrating.
QT-DoG: Quantization-Aware Training for Domain Generalization
Saqib Javed, Hieu Le, Mathieu Salzmann
International Conference on Machine Learning (ICML), 2025. [Preprint][Project Page][Code]
TL;DR: QT-DoG uses weight quantization as a regularizer to encourage flatter minima, enhancing
domain generalization. We also introduce ensembles of quantized models, achieving SoTA performance in DG.
Few-shot Personalized Scanpath Prediction
Ruoyu Xue, Jingyi Xu, Sounak Mondal, Hieu Le, Greg Zelinsky, Minh Hoai, Dimitris Samaras, 2025
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025. [Preprint]
Enhancing Compositional Text-to-Image Generation with Reliable Random Seeds
Shuangqi Li, Hieu Le, Jingyi Xu, Mathieu Salzmann, 2025
International Conference on Learning Representations (ICLR), 2025. [Preprint]
TL;DR: Noises are important for diffusion-based models. We show that some random seeds are much more reliable than others, which can be used to generate useful training data.
Learning to Count from Pseudo-Labeled Segmentation
Jingyi Xu, Hieu Le, Dimitris Samaras
Winter Conference on Applications of Computer Vision (WACV), 2025.
[Preprint]
Existing methods suffer from the counting-everything issues. We introduce a benchmark with multiple
countable objects in each image and show that we can mitigate this issues by using synthetic data.
Shadow Removal Refinement via Material-Consistent Shadow Edges
Shilin Hu, Hieu Le, ShahRukh Athar, Sagnik Das, Dimitris Samaras
Winter Conference on Applications of Computer Vision (WACV), 2025.
[Preprint][ Project Page] [ Testing Set ]
We proposed a new shadow removal method leveraging supervision from the shadow edges. Plus, we
introduced a new benchmark for shadow removal with no shadow-free images needed!
Assessing Sample Quality via the Latent Space of Generative Models
Jingyi Xu, Hieu Le, Dimitris Samaras European Conference on Computer
Vision (ECCV), 2024.
[ Preprint] [ Code]
[ Project Page]
Latent points located in dense regions of the latent manifold tend to produce higher-quality
samples, while those in sparser regions yield lower-quality ones.
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo
Density
Shuangqi Li, Chen Liu, Tong Zhang, Hieu Le, Sabine Susstrunk, Mathieu
Salzmann European Conference on Computer Vision (TMLR), 2024.
[ Openreview]
Neural Surface Localization for Unsigned Distance Fields
Federico Stella, Nicolas Talabot, Hieu Le, Pascal Fua European
Conference on Computer Vision (ECCV), 2024.
[ Preprint] [ Project Page]
Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object
Detection for Semi-Supervised Segmentation
Prantik Howlader, Hieu Le, Dimitris Samaras European Conference on
Computer Vision (ECCV), 2024.
[ Preprint] [ Code]
Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale
Patch-based Multi-Label Classifier
Prantik Howlader, Srijan Das, Hieu Le, Dimitris Samaras European
Conference on Computer Vision (ECCV), 2024.
[ Preprint] [ Code]
Generating Anatomically Accurate Heart Structures via Neural Implicit Fields
Jiancheng Yang, Ekaterina Sedykh, Jason Adhinarta, Hieu Le, Pascal Fua
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024 [Paper][Poster]
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier, Hieu Le, Pascal Fua
International Conference on Machine Learning (ICML), 2024.
[ Preprint] [ Code]
Zigzag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference
Nikita Durasov,Nik Dorndorf, Hieu Le, Pascal Fua Transactions on
Machine Learning Research
(TMLR), 2024.
[ Openreview] [ Code]
Zero-Shot Object Counting
Jingyi Xu, Hieu Le, Vu Nguyen, Viresh Ranjan, Dimitris Samaras
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[ Code] [ Stable-Diffusion extension]
Generating Features With Increased Crop-related Diversity For Few-shot Object
Detection
Jingyi Xu, Hieu Le, Dimitris Samaras
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[ Code (TBD)]
Generating Representative Samples for Few-Shot Classification
Jingyi Xu, Hieu Le
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
[Code] [Paper ] [ Blog
post ]
Physics-based Shadow Image Decomposition for Shadow Removal
Hieu Le, Dimitris Samaras.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[Github ] [Paper ]
A convolutional neural network architecture designed for the automated survey of
seabird colonies
Hieu Le, Dimitris Samaras, Heather J. Lynch
Remote Sensing in Ecology and Conservation , 2022.
[Paper ]
Variational Feature Disentangling for Fine-Grained Few-Shot Classification
Jingyi Xu, Hieu Le, Mingzhen Huang, ShahRukh Athar, Dimitris Samaras.
IEEE International Conference on Computer Vision (ICCV), 2021.
[PyTorch Code]
Aerial-trained deep learning networks for surveying cetaceans from satellite
imagery
Alex Borowicz, Hieu Le, Grant Humphries, Georg Nehls, Caroline Hoschle,
Vladislav Kosarev, Heather J. Lynch
Plos One , 2019.
[Paper ]
From Shadow Segmentation to Shadow Removal
Hieu Le, Dimitris Samaras.
European Conference on Computer Vision (ECCV), 2020.
[ Paper Project Page ]
Shadow Removal via Shadow Image Decomposition
Hieu Le, Dimitris Samaras.
International Conference on Computer Vision (ICCV), 2019.
[PaperProject Page ]
Weakly Labeling the Antarctic: The Penguin Colony Case
Hieu Le, Bento Gonçalves, Dimitris Samaras, Heather Lynch.
IEEE Conference on Computer Vision and Pattern Recognition - Workshop (CVPRW), 2019.
[Paper ]
A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation.
Hieu Le, Tomas F. Yago Vicente, Vu Nguyen, Minh Hoai, Dimitris Samaras.
European Conference on Computer Vision (ECCV), 2018.
[Paper]
Iterative Crowd Counting.
Viresh Ranjan, Hieu Le, and Minh Hoai.
European Conference on Computer Vision (ECCV), 2018.
[Paper]
Co-localization with Category-Consistent CNN Features and Geodesic Distance
Propagation
Hieu Le, Chen-Ping Yu, Gregory Zelinsky, Dimitris Samaras.
International Conference on Computer Vision - Workshop (ICCVW), 2017.
[Paper]
Geodesic Distance Histogram Feature for Video Segmentation
Hieu Le, Vu Nguyen, Chen-Ping Yu, Dimitris Samaras
Asian Conference on Computer Vision (ACCV), 2016. [link][Paper][Poster]
Efficient video segmentation using parametric graph partitioning
Chen-Ping Yu, Hieu Le, Gregory Zelinsky, Dimitris Samaras
International Conference on Computer Vision (ICCV), 2015.
[
paper]
Learning to Weight Parameters for Data Attribution
Shuangqi Li, Hieu Le, Jingyi Xu, Mathieu Salzmann, 2025 [Preprint]
We study data attribution in generative models, aiming to identify which training examples most influence a given output.
Improving Contrastive Learning for Referring Expression Counting
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 [Preprint]
We introduce a novel method for generating talking-head videos driven by audio input, incorporating
frame-wise emotion intensity to enhance realism and expressiveness in visual output. The intensity
is
pseudo-labeled and we introduce a latent space that facilitates generating videos with varied
frame-wise intensities.
We introduces a novel approach to referring expression segmentation with instance-awareness,
automatically finding and linking object instances in the image with the textual entities describing
them.
MedTet: An Online Motion Model for 4D Heart Reconstruction
TL;DR: This paper introduces a versatile framework for reconstructing 3D cardiac motion from limited real-time data, such as 2D slices or even 1D signals. Using a deformable tetrahedral grid, the method ensures anatomically consistent reconstructions suitable for intraoperative scenarios.
Services
Journal Reviewer:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
International Journal of Computer Vision (IJCV)
IEEE Transactions on Image Processing (TIP)
Computer Vision and Image Understanding (CVIU)
Journal of Photogrammetry and Remote Sensing (ISPRS)
Conference Reviewer:
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
International Conference on Computer Vision (ICCV)
European Conference on Computer Vision (ECCV)
AAAI Conference on Artificial Intelligence (AAAI)
Asian Conference on Computer Vision (ACCV)
The International Conference on Learning Representations (ICLR)
International Conference on Machine Learning (ICML)
Conference on Neural Information Processing Systems
(NeurISP)