DreamComposer: Controllable 3D Object Generation via Multi-View Conditions

no code implementations • 6 Dec 2023 • Yunhan Yang, Yukun Huang, Xiaoyang Wu, Yuan-Chen Guo, Song-Hai Zhang, Hengshuang Zhao, Tong He, Xihui Liu

However, due to the lack of information from multiple views, these works encounter difficulties in generating controllable novel views.

3D Object Reconstruction Novel View Synthesis +1

SAM3D: Segment Anything in 3D Scenes

1 code implementation • 6 Jun 2023 • Yunhan Yang, Xiaoyang Wu, Tong He, Hengshuang Zhao, Xihui Liu

In this work, we propose SAM3D, a novel framework that is able to predict masks in 3D point clouds by leveraging the Segment-Anything Model (SAM) in RGB images without further training or finetuning.

Segmentation

Data-Driven Network Neuroscience: On Data Collection and Benchmark

1 code implementation • NeurIPS 2023 • Jiaxing Xu, Yunhan Yang, David Tse Jung Huang, Sophi Shilpa Gururajapathy, Yiping Ke, Miao Qiao, Alan Wang, Haribalan Kumar, Josh McGeown, Eryn Kwon

This paper presents a comprehensive and quality collection of functional human brain network data for potential research in the intersection of neuroscience, machine learning, and graph analytics.

CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training

1 code implementation • ICCV 2023 • Tianyu Huang, Bowen Dong, Yunhan Yang, Xiaoshui Huang, Rynson W. H. Lau, Wanli Ouyang, WangMeng Zuo

To address this issue, we propose CLIP2Point, an image-depth pre-training method by contrastive learning to transfer CLIP to the 3D domain, and adapt it to point cloud classification.

Contrastive Learning Few-Shot Learning +4