2 citations · 6 across the 18 of their papers we have counts for
13 papers · 1 filter
PrEditor3D: Fast and Precise 3D Shape Editing
Ziya Erkoç, Can Gümeli, Chaoyang Wang +5
We propose a training-free approach to 3D editing that enables the editing of a single shape within a few minutes. The edited 3D mesh aligns well with the prompts, and remains iden…
4Real-Video: Learning Generalizable Photo-Realistic 4D Video Diffusion
Chaoyang Wang, Peiye Zhuang, Tuan Duc Ngo +7
We propose 4Real-Video, a novel framework for generating 4D videos, organized as a grid of video frames with both time and viewpoint axes. In this grid, each row contains frames sh…
DELTA: Dense Efficient Long-range 3D Tracking for any video
Tuan Duc Ngo, Peiye Zhuang, Chuang Gan +4
Tracking dense 3D motion from monocular videos remains challenging, particularly when aiming for pixel-level precision over long sequences. We introduce DELTA, a novel method that…
Pixel-Aligned Multi-View Generation with Depth Guided Decoder
Zhenggang Tang, Peiye Zhuang, Chaoyang Wang +5
The task of image-to-multi-view generation refers to generating novel views of an instance from a single image. Recent methods achieve this by extending text-to-image latent diffus…
VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control
Sherwin Bahmani, Ivan Skorokhodov, Aliaksandr Siarohin +9
Modern text-to-video synthesis models demonstrate coherent, photorealistic generation of complex videos from a text description. However, most existing models lack fine-grained con…
4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models
Heng Yu, Chaoyang Wang, Peiye Zhuang +6
Existing dynamic scene generation methods mostly rely on distilling knowledge from pre-trained 3D generative models, which are typically fine-tuned on synthetic object datasets. As…
GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement
Peiye Zhuang, Songfang Han, Chaoyang Wang +7
We propose a novel approach for 3D mesh reconstruction from multi-view images. Our method takes inspiration from large reconstruction models like LRM that use a transformer-based t…
3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting
Qihang Zhang, Yinghao Xu, Chaoyang Wang +4
Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This…
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace +8
The quality of the data and annotation upper-bounds the quality of a downstream model. While there exist large text corpora and image-text pairs, high-quality video-text data is mu…
Visual Concept-driven Image Generation with Text-to-Image Diffusion Model
Tanzila Rahman, Shweta Mahajan, Hsin-Ying Lee +3
Text-to-image (TTI) diffusion models have demonstrated impressive results in generating high-resolution images of complex and imaginative scenes. Recent approaches have further ext…
AToM: Amortized Text-to-Mesh using 2D Diffusion
Guocheng Qian, Junli Cao, Aliaksandr Siarohin +12
We introduce Amortized Text-to-Mesh (AToM), a feed-forward text-to-mesh framework optimized across multiple text prompts simultaneously. In contrast to existing text-to-3D methods…
Diffusion Priors for Dynamic View Synthesis from Monocular Videos
Chaoyang Wang, Peiye Zhuang, Aliaksandr Siarohin +4
Dynamic novel view synthesis aims to capture the temporal evolution of visual content within videos. Existing methods struggle to distinguishing between motion and structure, parti…
UpFusion: Novel View Diffusion from Unposed Sparse View Observations
Bharath Raj Nagoor Kani, Hsin-Ying Lee, Sergey Tulyakov +1
We propose UpFusion, a system that can perform novel view synthesis and infer 3D representations for an object given a sparse set of reference images without corresponding pose inf…