Zhenyu Li

Orcid: 0000-0003-2932-9179

Affiliations:
  • King Abdullah University of Science and Technology, Saudi Arabia


According to our database1, Zhenyu Li authored at least 29 papers between 2021 and 2025.

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Bibliography

2025
BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models?
CoRR, July, 2025

LaRI: Layered Ray Intersections for Single-view 3D Geometric Reasoning.
CoRR, April, 2025

PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation.
CoRR, January, 2025

The Devil is in the Quality: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection.
Proceedings of the IEEE International Conference on Robotics and Automation, 2025

PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation.
IEEE Trans. Image Process., 2024

Graph-DETR4D: Spatio-Temporal Graph Modeling for Multi-View 3D Object Detection.
IEEE Trans. Image Process., 2024

Amodal Depth Anything: Amodal Depth Estimation in the Wild.
CoRR, 2024

StereoCrafter-Zero: Zero-Shot Stereo Video Generation with Noisy Restart.
CoRR, 2024

ImmersePro: End-to-End Stereo Video Synthesis Via Implicit Disparity Learning.
CoRR, 2024

A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge - Multi-Task Robustness Track.
CoRR, 2024

AvatarMMC: 3D Head Avatar Generation and Editing with Multi-Modal Conditioning.
CoRR, 2024

PatchRefiner: Leveraging Synthetic Data for Real-Domain High-Resolution Monocular Metric Depth Estimation.
Proceedings of the Computer Vision - ECCV 2024, 2024

PatchFusion: An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
DepthFormer: Exploiting Long-range Correlation and Local Information for Accurate Monocular Depth Estimation.
Mach. Intell. Res., December, 2023

The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation.
CoRR, 2023

Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection.
CoRR, 2023

BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning with Noisy Data for Semi-Supervised 3D Object Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Self-Supervised Monocular Depth Estimation via Discrete Strategy and Uncertainty.
IEEE CAA J. Autom. Sinica, 2022

AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object Detection.
CoRR, 2022

Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile Devices.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-training.
Proceedings of the Computer Vision - ECCV 2022, 2022


Deformable Feature Aggregation for Dynamic Multi-modal 3D Object Detection.
Proceedings of the Computer Vision - ECCV 2022, 2022

SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-training for Spatial-Aware Visual Representations.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report.
CoRR, 2021


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