Youtian Lin

I work on the problem of 4D/3D reconstruction and generation. I am a incoming Ph.D. student of Prof. Yao Yao. I previously pursuing Ph.D. at Harbin Institute of Technology. Before that I received my M.S from Harbin Engineering University in 2021, where I was advised by Prof. Jian Guan.

Email / Scholar / Twitter (X) / Github

Research

My research focuses on combining computer vision and computer graphics technology, specifically 4D/3D reconstruction and generation, neural rendering, and other techniques, to develop real-world applications. I'm also interested in applying deep learning to computer vision and image processing.

	Gaussian-Flow: 4D Reconstruction with Dynamic 3D Gaussian Particle Youtian Lin, Zuozhuo Dai, Siyu Zhu, Yao Yao Arxiv, 2023 Github Project Page We propose an innovative point-based method for rapid dynamic scene reconstruction and real-time rendering from both multi-view and monocular videos, leveraging advancements in point-based 3D Gaussian Splatting (3DGS).
	Relightable 3D Gaussian: Real-time Point Cloud Relighting with BRDF Decomposition and Ray Tracing Jian Gao, Chun Gu, Youtian Lin, Hao Zhu, Xun Cao, Li Zhang, Yao Yao Arxiv, 2023 Github Project Page Utilizuing 3D Gaussian points to represent a scene, allowing for material and lighting decomposition, enabling real-time relighting, ray-tracing, and editing of the 3D point cloud with improved BRDF estimation and novel view rendering results.
	UniDream: Unifying Diffusion Priors for Relightable Text-to-3D Generation Zexiang Liu, Yangguang Li, Youtian Lin* Xin Yu, Sida Peng, Yan-Pei Cao, Xiaojuan Qi, Xiaoshui Huang, Ding Liang, Wanli Ouyang Arxiv, 2023 Github Project Page Use a dual-phase training process for albedo-normal aligned multi-view diffusion and reconstruction models, a progressive generation procedure for geometry and albedo-textures using Score Distillation Sample (SDS), and an innovative SDS application for finalizing Physically Based Rendering (PBR) generation with fixed albedo.
	Ced-NeRF: A Compact and Efficient Method for Dynamic Neural Radiance Fields Youtian Lin AAAI, 2024 Project Page We extend the Instant-NGP framework to support dynamic scenes, and show that it can be used to train a dynamic NeRF model that is both more compact and more efficient than prior work.
	EARL: An Elliptical Distribution aided Adaptive Rotation Label Assignment for Oriented Object Detection in Remote Sensing Images Jian Guan, Mingjie Xie, Youtian Lin, Guangjun He, Pengming Feng IEEE TGRS, 2023 Github Incorporating adaptive scale sampling, dynamic elliptical distribution aided sampling, and spatial distance weighting to enhance the selection of high-quality positive samples.
	TOSO: Student's-T Distribution Aided One-Stage Orientation Target Detection in Remote Sensing Images Pengming Feng, Youtian Lin, Jian Guan, Guangjun He, Huifeng Shi, Jonathon Chambers ICASSP, 2020 Utilizing a one-stage keypoint based network architecture and introducing a novel geometric transformation method to achieve orientation angle regression, along with incorporating Student's-t distribution to enhance performance
	IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection Youtian Lin, Pengming Feng, Jian Guan, Wenwu Wang, Jonathon Chambers Arxiv, 2019 We addressing the challenges of computational complexity in two-stage detectors by employing a per-pixel prediction approach with a geometric transformation, a branch interactive module, and an enhanced intersection over union (IoU) loss.
	A Dynamic End-To-End Fusion Filter For Local Climate Zone Classification Using Sar And Multi-Spectrum Remote Sensing Data Pengming Feng, Youtian Lin, Guangjun He, Jian Guan, Huifeng Shi IGARSS, 2020 Use a dynamic end-to-end fusion filter to integrate different bands in SAR and multi-spectrum data to enhances the fusion accuracy by a flexible dynamic operation.
	Embranchment Cnn Based Local Climate Zone Classification Using Sar And Multispectral Remote Sensing Data Pengming Feng, Youtian Lin, Jian Guan, Guangjun He, Zhenghuan Xia, Huifeng Shi IGARSS, 2019 Considering about the difference in imaging mechanism between SAR and multispectral data, features from both resources are extracted in different branches separately according to the physical properties of each band.

Project

threestudio-3dgs
The Gaussian Splatting extension for threestudio.

taichi-nerfs
A PyTorch + Taichi implementation of instant-ngp NeRF training pipeline. For more details about modeling, please checkout this blog.

taichi-ngp-renderer
A Instant-NGP renderer implemented using Taichi, written entirely in Python. No CUDA!

nerfacc
A PyTorch Nerf acceleration toolbox for both training and inference. (As a contributor, I have implemented a fast ngp rendering in CUDA)

Source code borrow from jonbarron.