3 citations · 5 across the 10 of their papers we have counts for
11 papers
ReaDiT Guidance: Control for Image and Video Generation using Diffusion Transformer Features
Jay Mahajan, Chang Liu, Rauf Makharov +3
We present DiT Readout (ReaDiT) Guidance, a lightweight framework for controlling generation with Diffusion Transformer (DiT) models via their internal feature representations. Rea…
AniGS: Bridging Rendering and Diffusion Prior for 3D Scene Animation
Yen-Chi Cheng, Chen Gao, Chuhan Chen +8
Novel view rendering of large and complex reconstructed scenes is becoming increasingly photorealistic. However, most reconstructions remain static and lack the ambient motion that…
NoPo-Avatar: Generalizable and Animatable Avatars from Sparse Inputs without Human Poses
Jing Wen, Alexander G. Schwing, Shenlong Wang
We tackle the task of recovering an animatable 3D human avatar from a single or a sparse set of images. For this task, beyond a set of images, many prior state-of-the-art methods u…
3D-Fixup: Advancing Photo Editing with 3D Priors
Yen-Chi Cheng, Krishna Kumar Singh, Jae Shin Yoon +5
Despite significant advances in modeling image priors via diffusion models, 3D-aware image editing remains challenging, in part because the object is only specified via a single im…
Studying Classifier(-Free) Guidance From a Classifier-Centric Perspective
Xiaoming Zhao, Alexander G. Schwing
Classifier-free guidance has become a staple for conditional generation with denoising diffusion models. However, a comprehensive understanding of classifier-free guidance is still…
LIFe-GoM: Generalizable Human Rendering with Learned Iterative Feedback Over Multi-Resolution Gaussians-on-Mesh
Jing Wen, Alexander G. Schwing, Shenlong Wang
Generalizable rendering of an animatable human avatar from sparse inputs relies on data priors and inductive biases extracted from training on large data to avoid scene-specific op…
MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds
Zhenggang Tang, Yuchen Fan, Dilin Wang +4
Recent sparse multi-view scene reconstruction advances like DUSt3R and MASt3R no longer require camera calibration and camera pose estimation. However, they only process a pair of…
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…
NeRFDeformer: NeRF Transformation from a Single View via 3D Scene Flows
Zhenggang Tang, Zhongzheng Ren, Xiaoming Zhao +4
We present a method for automatically modifying a NeRF representation based on a single observation of a non-rigid transformed version of the original scene. Our method defines the…
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-Mesh
Jing Wen, Xiaoming Zhao, Zhongzheng Ren +2
We introduce GoMAvatar, a novel approach for real-time, memory-efficient, high-quality animatable human modeling. GoMAvatar takes as input a single monocular video to create a digi…
Virtual Pets: Animatable Animal Generation in 3D Scenes
Yen-Chi Cheng, Chieh Hubert Lin, Chaoyang Wang +5
Toward unlocking the potential of generative models in immersive 4D experiences, we introduce Virtual Pet, a novel pipeline to model realistic and diverse motions for target animal…