collaborators

6 papers

cs.CV2025

Fancy123: One Image to High-Quality 3D Mesh Generation via Plug-and-Play Deformation

Qiao Yu, Xianzhi Li, Yuan Tang +4

Generating 3D meshes from a single image is an important but ill-posed task. Existing methods mainly adopt 2D multiview diffusion models to generate intermediate multiview images,…

cs.CV2025

PointDreamer: Zero-shot 3D Textured Mesh Reconstruction from Colored Point Cloud

Qiao Yu, Xianzhi Li, Yuan Tang +4

Faithfully reconstructing textured meshes is crucial for many applications. Compared to text or image modalities, leveraging 3D colored point clouds as input (colored-PC-to-mesh) o…

cs.CV2025

SASep: Saliency-Aware Structured Separation of Geometry and Feature for Open Set Learning on Point Clouds

Jinfeng Xu, Xianzhi Li, Yuan Tang +5

Recent advancements in deep learning have greatly enhanced 3D object recognition, but most models are limited to closed-set scenarios, unable to handle unknown samples in real-worl…

cs.CV2025

More Text, Less Point: Towards 3D Data-Efficient Point-Language Understanding

Yuan Tang, Xu Han, Xianzhi Li +5

Enabling Large Language Models (LLMs) to comprehend the 3D physical world remains a significant challenge. Due to the lack of large-scale 3D-text pair datasets, the success of LLMs…

cs.CV2024

PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation

Jinfeng Xu, Siyuan Yang, Xianzhi Li +4

Existing point cloud semantic segmentation networks cannot identify unknown classes and update their knowledge, due to a closed-set and static perspective of the real world, which…

cs.CV2024

MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors

Yuan Tang, Xu Han, Xianzhi Li +4

Large 2D vision-language models (2D-LLMs) have gained significant attention by bridging Large Language Models (LLMs) with images using a simple projector. Inspired by their success…