2 citations · 5 across the 23 of their papers we have counts for
26 papers
SceneConductor: 3D Scene Generation from a Single Image with Multi-Agent Orchestration
Jeonghwan Kim, Yushi Lan, Yongwei Chen +3
Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual…
ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation
Yu Zhang, Yidi Shao, Wenqi Ouyang +5
Unified and scalable Transformers have recently achieved remarkable success in modeling diverse phenomena traditionally associated with computer graphics, such as 3D visual effects…
PnP-U3D: Plug-and-Play 3D Framework Bridging Autoregression and Diffusion for Unified Understanding and Generation
Yongwei Chen, Tianyi Wei, Yushi Lan +4
The rapid progress of large multimodal models has inspired efforts toward unified frameworks that couple understanding and generation. While such paradigms have shown remarkable su…
4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere
Yihang Luo, Shangchen Zhou, Yushi Lan +2
We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple motion from geometry or produce lim…
Video4Spatial: Towards Visuospatial Intelligence with Context-Guided Video Generation
Zeqi Xiao, Yiwei Zhao, Lingxiao Li +6
We investigate whether video generative models can exhibit visuospatial intelligence, a capability central to human cognition, using only visual data. To this end, we present Video…
Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers
Yifan Zhou, Zeqi Xiao, Tianyi Wei +2
Diffusion Transformers (DiTs) set the state of the art in visual generation, yet their quadratic self-attention cost fundamentally limits scaling to long token sequences. Recent To…
Boosting Monocular Metric Depth Estimation via Bokeh Rendering
Hangwei Zhang, Armando Fortes, Tianyi Wei +1
Bokeh rendering and depth estimation share a fundamental optical connection, yet existing methods fail to fully exploit this reciprocity. Conventional bokeh pipelines rely heavily…
ArtiLatent: Realistic Articulated 3D Object Generation via Structured Latents
Honghua Chen, Yushi Lan, Yongwei Chen +1
We propose ArtiLatent, a generative framework that synthesizes human-made 3D objects with fine-grained geometry, accurate articulation, and realistic appearance. Our approach joint…
Towards Geometry-Grounded Dense Semantic Matching with VGGT Priors
Songlin Yang, Tianyi Wei, Yushi Lan +3
Semantic matching aims to establish pixel-level correspondences between instances of the same category and represents a fundamental task in computer vision. Existing approaches suf…
STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer
Yushi Lan, Yihang Luo, Fangzhou Hong +7
We present STream3R, a novel approach to 3D reconstruction that reformulates pointmap prediction as a decoder-only Transformer problem. Existing state-of-the-art methods for multi-…
FastMesh: Efficient Artistic Mesh Generation via Component Decoupling
Jeonghwan Kim, Yushi Lan, Armando Fortes +2
Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substan…
WorldMem: Long-term Consistent World Simulation with Memory
Zeqi Xiao, Yushi Lan, Yifan Zhou +4
World simulation has gained increasing popularity due to its ability to model virtual environments and predict the consequences of actions. However, the limited temporal context wi…
FreeFlux: Understanding and Exploiting Layer-Specific Roles in RoPE-Based MMDiT for Versatile Image Editing
Tianyi Wei, Yifan Zhou, Dongdong Chen +1
The integration of Rotary Position Embedding (RoPE) in Multimodal Diffusion Transformer (MMDiT) has significantly enhanced text-to-image generation quality. However, the fundamenta…
Alias-Free Latent Diffusion Models: Improving Fractional Shift Equivariance of Diffusion Latent Space
Yifan Zhou, Zeqi Xiao, Shuai Yang +1
Latent Diffusion Models (LDMs) are known to have an unstable generation process, where even small perturbations or shifts in the input noise can lead to significantly different out…
Bokeh Diffusion: Defocus Blur Control in Text-to-Image Diffusion Models
Armando Fortes, Tianyi Wei, Shangchen Zhou +1
Recent advances in large-scale text-to-image models have revolutionized creative fields by generating visually captivating outputs from textual prompts; however, while traditional…
Textured 3D Regenerative Morphing with 3D Diffusion Prior
Songlin Yang, Yushi Lan, Honghua Chen +1
Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative…
3DEnhancer: Consistent Multi-View Diffusion for 3D Enhancement
Yihang Luo, Shangchen Zhou, Yushi Lan +2
Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model gener…
Trajectory Attention for Fine-grained Video Motion Control
Zeqi Xiao, Wenqi Ouyang, Yifan Zhou +4
Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized v…
Enhancing MMDiT-Based Text-to-Image Models for Similar Subject Generation
Tianyi Wei, Dongdong Chen, Yifan Zhou +1
Representing the cutting-edge technique of text-to-image models, the latest Multimodal Diffusion Transformer (MMDiT) largely mitigates many generation issues existing in previous m…
GaussianAnything: Interactive Point Cloud Flow Matching For 3D Object Generation
Yushi Lan, Shangchen Zhou, Zhaoyang Lyu +5
While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper intro…
MvDrag3D: Drag-based Creative 3D Editing via Multi-view Generation-Reconstruction Priors
Honghua Chen, Yushi Lan, Yongwei Chen +2
Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Ex…
I2VEdit: First-Frame-Guided Video Editing via Image-to-Video Diffusion Models
Wenqi Ouyang, Yi Dong, Lei Yang +2
The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional chall…
MVIP-NeRF: Multi-view 3D Inpainting on NeRF Scenes via Diffusion Prior
Honghua Chen, Chen Change Loy, Xingang Pan
Despite the emergence of successful NeRF inpainting methods built upon explicit RGB and depth 2D inpainting supervisions, these methods are inherently constrained by the capabiliti…
Video Diffusion Models are Training-free Motion Interpreter and Controller
Zeqi Xiao, Yifan Zhou, Shuai Yang +1
Video generation primarily aims to model authentic and customized motion across frames, making understanding and controlling the motion a crucial topic. Most diffusion-based studie…