17 citations · 20 across the 15 of their papers we have counts for
18 papers
LLM2R: From Large Language Models to 3D Reassemblers
Zhouhan Zhong, Qiuhong Shen, Xingyi Yang +2
3D part assembly aims to reconstruct a complete shape from a set of unassembled parts by predicting a rigid SE(3) transformation for each part. Because the placement of a part is r…
Visual Geometry Transformer in the Wild: Distractor-Free 3D Reconstruction
Tianbo Pan, Xingyi Yang, Shizun Wang +1
Current end-to-end multi-view 3D reconstruction methods achieve impressive results, but rely on a restrictive static assumption: the scenes is entire distractor-free with perfect c…
WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion
Hanyang Kong, Xingyi Yang, Xiaoxu Zheng +1
Generating long-range, geometrically consistent video presents a fundamental dilemma: while consistency demands strict adherence to 3D geometry in pixel space, state-of-the-art gen…
C4D: 4D Made from 3D through Dual Correspondences
Shizun Wang, Zhenxiang Jiang, Xingyi Yang +1
Recovering 4D from monocular video, which jointly estimates dynamic geometry and camera poses, is an inevitably challenging problem. While recent pointmap-based 3D reconstruction m…
Don't Forget the Nonlinearity: Unlocking Activation Functions in Efficient Fine-Tuning
Bo Yin, Xingyi Yang, Xinchao Wang
Existing parameter-efficient fine-tuning (PEFT) methods primarily adapt weight matrices while keeping activation functions fixed. We introduce \textbf{NoRA}, the first PEFT framewo…
Test3R: Learning to Reconstruct 3D at Test Time
Yuheng Yuan, Qiuhong Shen, Shizun Wang +2
Dense matching methods like DUSt3R regress pairwise pointmaps for 3D reconstruction. However, the reliance on pairwise prediction and the limited generalization capability inherent…
Minute-Long Videos with Dual Parallelisms
Zeqing Wang, Bowen Zheng, Xingyi Yang +3
Diffusion Transformer (DiT)-based video diffusion models generate high-quality videos at scale but incur prohibitive processing latency and memory costs for long videos. To address…
Flash Sculptor: Modular 3D Worlds from Objects
Yujia Hu, Songhua Liu, Xingyi Yang +1
Existing text-to-3D and image-to-3D models often struggle with complex scenes involving multiple objects and intricate interactions. Although some recent attempts have explored suc…
1000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering
Yuheng Yuan, Qiuhong Shen, Xingyi Yang +1
4D Gaussian Splatting (4DGS) has recently gained considerable attention as a method for reconstructing dynamic scenes. Despite achieving superior quality, 4DGS typically requires s…
GraphBridge: Towards Arbitrary Transfer Learning in GNNs
Li Ju, Xingyi Yang, Qi Li +1
Graph neural networks (GNNs) are conventionally trained on a per-domain, per-task basis. It creates a significant barrier in transferring the acquired knowledge to different, heter…
Efficient Gaussian Splatting for Monocular Dynamic Scene Rendering via Sparse Time-Variant Attribute Modeling
Hanyang Kong, Xingyi Yang, Xinchao Wang
Rendering dynamic scenes from monocular videos is a crucial yet challenging task. The recent deformable Gaussian Splatting has emerged as a robust solution to represent real-world…
Few-shot Implicit Function Generation via Equivariance
Suizhi Huang, Xingyi Yang, Hongtao Lu +1
Implicit Neural Representations (INRs) have emerged as a powerful framework for representing continuous signals. However, generating diverse INR weights remains challenging due to…
Language Model as Visual Explainer
Xingyi Yang, Xinchao Wang
In this paper, we present Language Model as Visual Explainer LVX, a systematic approach for interpreting the internal workings of vision models using a tree-structured linguistic e…
Neural Metamorphosis
Xingyi Yang, Xinchao Wang
This paper introduces a new learning paradigm termed Neural Metamorphosis (NeuMeta), which aims to build self-morphable neural networks. Contrary to crafting separate models for di…
Kolmogorov-Arnold Transformer
Xingyi Yang, Xinchao Wang
Transformers stand as the cornerstone of mordern deep learning. Traditionally, these models rely on multi-layer perceptron (MLP) layers to mix the information between channels. In…
FlashSplat: 2D to 3D Gaussian Splatting Segmentation Solved Optimally
Qiuhong Shen, Xingyi Yang, Xinchao Wang
This study addresses the challenge of accurately segmenting 3D Gaussian Splatting from 2D masks. Conventional methods often rely on iterative gradient descent to assign each Gaussi…
Focus on Neighbors and Know the Whole: Towards Consistent Dense Multiview Text-to-Image Generator for 3D Creation
Bonan Li, Zicheng Zhang, Xingyi Yang +1
Generating dense multiview images from text prompts is crucial for creating high-fidelity 3D assets. Nevertheless, existing methods struggle with space-view correspondences, result…
DragGaussian: Enabling Drag-style Manipulation on 3D Gaussian Representation
Sitian Shen, Jing Xu, Yuheng Yuan +3
User-friendly 3D object editing is a challenging task that has attracted significant attention recently. The limitations of direct 3D object editing without 2D prior knowledge have…