Hieu Le (Hiếu Lê) Assistant Professor University of North Carolina - Charlotte Charlotte Computer Vision Lab I am an Assistant Professor at UNC Charlotte and co-founder of the Charlotte Computer Vision Lab. Prior to UNC Charlotte, I earned my PhD at Stony Brook University, worked at Amazon Robotics and EPFL. My research centers on controllable and reliable machine vision, with the goal of building models that can follow constraints, provide interpretable reasoning, and make predictions with calibrated uncertainty. Email Google Scholar CV

News

[2026] InstAlign is accepted to CVPR 2026 - Workshop on Pixel-level Video Understanding in the Wild

[2026] Two papers have been accepted to CVPR 2026: Personalized Image Descriptions and MS-Temba

[2026] Learning to Weight Parameters for Data Attribution has been accepted to ICLR 2026.

[2026] CORA has been accepted to WACV 2026.

[2025] Part-SDF has been accepted to TMLR 2025.

[2025] Iterative meshing of UDFs has been accepted to NeurIPS 2025.

[2025] Two papers have been accepted to ICCV 2025, both are selected for Oral presentation (64 out of 11,239 submissions).

[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.

[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.

Services

Journal Reviewer:

Conference Reviewer:

Awards