32 citations · 103 across the 30 of their papers we have counts for
27 papers · 1 filter
Geometry-Instructed Video Editing
Chirui Chang, Xiaoyang Lyu, Yi-Hua Huang +7
Object-level geometric edits, including translating, rotating, scaling, duplicating, or removing an object, are routine operations in digital content creation (DCC) workflows, yet…
Softmax-GS: Generalized Gaussians Learning When to Blend or Bound
Chen Ziwen, Peng Wang, Hao Tan +2
3D Gaussian Splatting (3D GS) is widely adopted for novel view synthesis due to its high training and rendering efficiency. However, its efficiency relies on the key assumption tha…
OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation
Yuheng Liu, Xin Lin, Xinke Li +9
Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthe…
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…
E-RayZer: Self-supervised 3D Reconstruction as Spatial Visual Pre-training
Qitao Zhao, Hao Tan, Qianqian Wang +5
Self-supervised pre-training has driven rapid progress in foundation models for language, 2D images, and video, yet remains largely unexplored for learning 3D-aware representations…
Long-LRM++: Preserving Fine Details in Feed-Forward Wide-Coverage Reconstruction
Chen Ziwen, Hao Tan, Peng Wang +2
Recent advances in generalizable Gaussian splatting (GS) have enabled feed-forward reconstruction of scenes from tens of input views. Long-LRM notably scales this paradigm to 32 in…
SplatPainter: Interactive Authoring of 3D Gaussians from 2D Edits via Test-Time Training
Yang Zheng, Hao Tan, Kai Zhang +4
The rise of 3D Gaussian Splatting has revolutionized photorealistic 3D asset creation, yet a critical gap remains for their interactive refinement and editing. Existing approaches…
AlignTok: Aligning Visual Foundation Encoders to Tokenizers for Diffusion Models
Bowei Chen, Sai Bi, Hao Tan +6
In this work, we propose aligning pretrained visual encoders to serve as tokenizers for latent diffusion models in image generation. Unlike training a variational autoencoder (VAE)…
4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time
Ziqiao Ma, Xuweiyi Chen, Shoubin Yu +10
Can we scale 4D pretraining to learn general space-time representations that reconstruct an object from a few views at some times to any view at any time? We provide an affirmative…
RayZer: A Self-supervised Large View Synthesis Model
Hanwen Jiang, Hao Tan, Peng Wang +8
We present RayZer, a self-supervised multi-view 3D Vision model trained without any 3D supervision, i.e., camera poses and scene geometry, while exhibiting emerging 3D awareness. C…
RigAnything: Template-Free Autoregressive Rigging for Diverse 3D Assets
Isabella Liu, Zhan Xu, Wang Yifan +5
We present RigAnything, a novel autoregressive transformer-based model, which makes 3D assets rig-ready by probabilistically generating joints and skeleton topologies and assigning…
Turbo3D: Ultra-fast Text-to-3D Generation
Hanzhe Hu, Tianwei Yin, Fujun Luan +6
We present Turbo3D, an ultra-fast text-to-3D system capable of generating high-quality Gaussian splatting assets in under one second. Turbo3D employs a rapid 4-step, 4-view diffusi…
RandAR: Decoder-only Autoregressive Visual Generation in Random Orders
Ziqi Pang, Tianyuan Zhang, Fujun Luan +5
We introduce RandAR, a decoder-only visual autoregressive (AR) model capable of generating images in arbitrary token orders. Unlike previous decoder-only AR models that rely on a p…
Buffer Anytime: Zero-Shot Video Depth and Normal from Image Priors
Zhengfei Kuang, Tianyuan Zhang, Kai Zhang +7
We present Buffer Anytime, a framework for estimation of depth and normal maps (which we call geometric buffers) from video that eliminates the need for paired video--depth and vid…
KFC-W: Generating 3D-Consistent Videos from Unposed Internet Photos
Gene Chou, Kai Zhang, Sai Bi +5
We address the problem of generating videos from unposed internet photos. A handful of input images serve as keyframes, and our model interpolates between them to simulate a path m…
RelitLRM: Generative Relightable Radiance for Large Reconstruction Models
Tianyuan Zhang, Zhengfei Kuang, Haian Jin +9
We propose RelitLRM, a Large Reconstruction Model (LRM) for generating high-quality Gaussian splatting representations of 3D objects under novel illuminations from sparse (4-8) pos…
LVSM: A Large View Synthesis Model with Minimal 3D Inductive Bias
Haian Jin, Hanwen Jiang, Hao Tan +6
We propose the Large View Synthesis Model (LVSM), a novel transformer-based approach for scalable and generalizable novel view synthesis from sparse-view inputs. We introduce two a…
Long-LRM: Long-sequence Large Reconstruction Model for Wide-coverage Gaussian Splats
Chen Ziwen, Hao Tan, Kai Zhang +5
We propose Long-LRM, a feed-forward 3D Gaussian reconstruction model for instant, high-resolution, 360° wide-coverage, scene-level reconstruction. Specifically, it takes in 32 inpu…
LRM-Zero: Training Large Reconstruction Models with Synthesized Data
Desai Xie, Sai Bi, Zhixin Shu +7
We present LRM-Zero, a Large Reconstruction Model (LRM) trained entirely on synthesized 3D data, achieving high-quality sparse-view 3D reconstruction. The core of LRM-Zero is our p…
GS-LRM: Large Reconstruction Model for 3D Gaussian Splatting
Kai Zhang, Sai Bi, Hao Tan +4
We propose GS-LRM, a scalable large reconstruction model that can predict high-quality 3D Gaussian primitives from 2-4 posed sparse images in 0.23 seconds on single A100 GPU. Our m…
MeshLRM: Large Reconstruction Model for High-Quality Meshes
Xinyue Wei, Kai Zhang, Sai Bi +6
We propose MeshLRM, a novel LRM-based approach that can reconstruct a high-quality mesh from merely four input images in less than one second. Different from previous large reconst…
Template-Free Single-View 3D Human Digitalization with Diffusion-Guided LRM
Zhenzhen Weng, Jingyuan Liu, Hao Tan +4
Reconstructing 3D humans from a single image has been extensively investigated. However, existing approaches often fall short on capturing fine geometry and appearance details, hal…
Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning
Desai Xie, Jiahao Li, Hao Tan +6
Multi-view diffusion models, obtained by applying Supervised Finetuning (SFT) to text-to-image diffusion models, have driven recent breakthroughs in text-to-3D research. However, d…
PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction
Peng Wang, Hao Tan, Sai Bi +6
We propose a Pose-Free Large Reconstruction Model (PF-LRM) for reconstructing a 3D object from a few unposed images even with little visual overlap, while simultaneously estimating…