1 citations · 1 across the 8 of their papers we have counts for
8 papers
Realistic Evaluation of Model Merging for Compositional Generalization
Derek Tam, Yash Kant, Brian Lester +2
Merging has become a widespread way to cheaply combine individual models into a single model that inherits their capabilities and attains better performance. This popularity has sp…
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…
SPAD : Spatially Aware Multiview Diffusers
Yash Kant, Ziyi Wu, Michael Vasilkovsky +7
We present SPAD, a novel approach for creating consistent multi-view images from text prompts or single images. To enable multi-view generation, we repurpose a pretrained 2D diffus…
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…
iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis
Yash Kant, Aliaksandr Siarohin, Michael Vasilkovsky +4
We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achie…
CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos
Tianshu Kuai, Akash Karthikeyan, Yash Kant +2
Animating an object in 3D often requires an articulated structure, e.g. a kinematic chain or skeleton of the manipulated object with proper skinning weights, to obtain smooth movem…