1 citations · 2 across the 9 of their papers we have counts for
9 papers
GaussianSelector: Lightweight Human-Guided Object Selection in 3D Gaussian Splatting with Graph Optimization
Baihan Yang, Tiexin Li, Yuheng Liu +4
Selecting a complete 3D object from a reconstructed scene with minimal user effort is essential for practical scene editing and embodied interaction. Existing 3DGS-based methods ei…
RecGen3D: Reconstruction-Guided 3D Generation in a Shared Canonical Space
Zhisheng Huang, Jiahao Chen, Cheng Lin +10
Sparse-view 3D modeling represents a fundamental tension between reconstruction fidelity and generative plausibility. While feed-forward reconstruction excels in efficiency and inp…
tttLRM: Test-Time Training for Long Context and Autoregressive 3D Reconstruction
Chen Wang, Hao Tan, Wang Yifan +6
We propose tttLRM, a novel large 3D reconstruction model that leverages a Test-Time Training (TTT) layer to enable long-context, autoregressive 3D reconstruction with linear comput…
Data-Chain Backdoor: Do You Trust Diffusion Models as Generative Data Supplier?
Junchi Lu, Xinke Li, Yuheng Liu +1
The increasing use of generative models such as diffusion models for synthetic data augmentation has greatly reduced the cost of data collection and labeling in downstream percepti…
Learning Unified Representation of 3D Gaussian Splatting
Yuelin Xin, Yuheng Liu, Xiaohui Xie +1
A well-designed vectorized representation is crucial for the learning systems natively based on 3D Gaussian Splatting. While 3DGS enables efficient and explicit 3D reconstruction,…
VRMDiff: Text-Guided Video Referring Matting Generation of Diffusion
Lehan Yang, Jincen Song, Tianlong Wang +4
We propose a new task, video referring matting, which obtains the alpha matte of a specified instance by inputting a referring caption. We treat the dense prediction task of mattin…
Controllable 3D Outdoor Scene Generation via Scene Graphs
Yuheng Liu, Xinke Li, Yuning Zhang +6
Three-dimensional scene generation is crucial in computer vision, with applications spanning autonomous driving, gaming and the metaverse. Current methods either lack user control…
Enhancing Sampling Protocol for Point Cloud Classification Against Corruptions
Chongshou Li, Pin Tang, Xinke Li +2
Established sampling protocols for 3D point cloud learning, such as Farthest Point Sampling (FPS) and Fixed Sample Size (FSS), have long been relied upon. However, real-world data…
Pyramid Diffusion for Fine 3D Large Scene Generation
Yuheng Liu, Xinke Li, Xueting Li +3
Diffusion models have shown remarkable results in generating 2D images and small-scale 3D objects. However, their application to the synthesis of large-scale 3D scenes has been rar…