Qijian Tian

I'm a fourth-year Ph.D. student in Computer Science at Shanghai Jiao Tong University (SJTU), advised by Prof. Lizhuang Ma in the Digital Media & Computer Vision Laboratory (DMCV). I also receive supervision from Dr. Xin Tan, who is based at East China Normal University (ECNU).

Prior to starting my Ph.D., I received my Bachelor's degree in Computer Science from Beihang University (BUAA). I also worked as an intern at Baidu.

Email / Scholar / Github

Research

My research interests involve multimodal large language models (MLLM) and 3D vision.
I am currently interested in MLLM post-training, agentic RL, and world models.
I have previously conducted some work in 2D/3D scene understanding, especially in scene parsing and 3D Gaussian splatting.

2026.08: I am currently looking for collaboration / internship opportunities related to MLLM. Feel free to contact me!

	FLEG: Feed-Forward Language Embedded Gaussian Splatting from Any Views via Compact Semantic Representation Qijian Tian, Xin Tan, Jiayu Ying, Xuhong Wang, Yuan Xie, Lizhuang Ma *ECCV 2026* project page / arXiv A feed-forward network that reconstructs language-embedded 3D Gaussians from arbitrary uncalibrated and unposed images with a compact semantic representation that avoids per-Gaussian language embedding and significantly reduces storage overhead.
	S2D: Sparse to Dense Lifting for 3D Reconstruction with Minimal Inputs Yuzhou Ji, Qijian Tian, He Zhu, Xiaoqi Jiang, Guangzhi Cao, Lizhuang Ma, Yuan Xie, Xin Tan *CVPR 2026* project page / arXiv A sparse-to-dense lifting pipeline that bridges point clouds and 3D Gaussian Splatting via a one-step diffusion model, enabling high-quality 3DGS reconstruction with minimal inputs.
	DrivingForward: Feed-forward 3D Gaussian Splatting for Driving Scene Reconstruction from Flexible Surround-view Input Qijian Tian, Xin Tan, Yuan Xie, Lizhuang Ma *AAAI 2025* project page / arXiv A feed-forward Gaussian Splatting model that reconstructs driving scenes from flexible sparse surround-view input.
	DANIM: Domain Adaptation Network with Intermediate Domain Masking for Night-time Scene Parsing Qijian Tian, Sen Wang, Ran Yi, Zufeng Zhang, Bin Sheng, Xin Tan, Lizhuang Ma Pattern Recognition 2025 A novel domain adaptation network for night-time scene parsing that bridges the day-night domain gap using an intermediate domain.
	Generalized Category Discovery in Semantic Segmentation Zhengyuan Peng, Qijian Tian, JianQing Xu, Yizhang Jin, Xuequan Lu, Xin Tan, Yuan Xie, Lizhuang Ma arXiv 2023 arXiv A novel setting called Generalized Category Discovery in Semantic Segmentation (GCDSS). Given prior knowledge from a labeled set of base classes, our method aims to segment unlabeled images that contain pixels of the base class or novel class.

This homepage's source code is from Jon Barron's website.