Yuanhui Huang

I am a second year Ph.D student in i-VisionGroup in the Department of Automation, Tsinghua University, advised by Prof. Jiwen Lu . In 2022, I received my BS degree from the Department of Electronic Engineering, Tsinghua University. I am interested in computer vision and deep learning. My current research focuses on autonomous driving, representation learning and generative models.

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Publications

*Equal contribution    ^†Project leader.

GaussianFormer proposes the 3D semantic Gaussians as a more efficient object-centric representation for driving scenes compared with 3D occupancy.

OccWorld models the joint evolutions of 3D scenes and ego movements and paves the way for interpretable end-to-end large driving models.

SelfOcc is the first self-supervised work that produces reasonable 3D occupancy for surround cameras.

As the first 2D-projection-based method on the 3D semantic occupancy prediction task, PointOcc significantly outperforms all other methods by a large margin with a much faster speed.

Given only surround-camera motorcycle RGB images barrier as inputs, our model (trained using trailer only sparse traffic cone LiDAR point supervision) can predict the semantic occupancy for all volumes in the 3D space.

This paper propose a hierarchical concept refiner to construct multiple levels of concept embeddings of an image and them pull closer the distance of the corresponding concepts to facilitate the cross-level semantic structure of the image representations.

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