Mickaël Chen

According to our database1, Mickaël Chen authored at least 28 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights.
CoRR, June, 2025

VaViM and VaVAM: Autonomous Driving through Video Generative Modeling.
CoRR, February, 2025

GaussRender: Learning 3D Occupancy with Gaussian Rendering.
CoRR, February, 2025

Halton Scheduler for Masked Generative Image Transformer.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
LOGen: Toward Lidar Object Generation by Point Diffusion.
CoRR, 2024

Annealed Winner-Takes-All for Motion Forecasting.
CoRR, 2024

Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Valeo4Cast: A Modular Approach to End-to-End Forecasting.
Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

Reliability in Semantic Segmentation: Can We Use Synthetic Data?
Proceedings of the Computer Vision - ECCV 2024, 2024

PointBeV: A Sparse Approach to BeV Predictions.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Manipulating Trajectory Prediction with Backdoors.
CoRR, 2023

A Pytorch Reproduction of Masked Generative Image Transformer.
CoRR, 2023

Challenges of Using Real-World Sensory Inputs for Motion Forecasting in Autonomous Driving.
CoRR, 2023

Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unifying GANs and Score-Based Diffusion as Generative Particle Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DiffHPE: Robust, Coherent 3D Human Pose Lifting with Diffusion.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

OCTET: Object-aware Counterfactual Explanations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
A Neural Tangent Kernel Perspective of GANs.
Proceedings of the International Conference on Machine Learning, 2022

STEEX: Steering Counterfactual Explanations with Semantics.
Proceedings of the Computer Vision - ECCV 2022, 2022

Raising context awareness in motion forecasting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2020
Learning with weak supervision using deep generative networks. (Apprentissage en supervision faible par l'emploi de réseaux génératifs profonds).
PhD thesis, 2020

Adversarial learning for modeling human motion.
Vis. Comput., 2020

Stochastic Latent Residual Video Prediction.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Unsupervised Object Segmentation by Redrawing.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Multi-View Data Generation Without View Supervision.
Proceedings of the 6th International Conference on Learning Representations, 2018

transferring style in motion capture sequences with adversarial learning.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Multi-view Generative Adversarial Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017


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