30 citations · 113 across the 35 of their papers we have counts for
35 papers
Extracting Training Data from Document-Based VQA Models
Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr +2
Vision-Language Models (VLMs) have made remarkable progress in document-based Visual Question Answering (i.e., responding to queries about the contents of an input document provide…
Toward a Diffusion-Based Generalist for Dense Vision Tasks
Yue Fan, Yongqin Xian, Xiaohua Zhai +4
Building generalized models that can solve many computer vision tasks simultaneously is an intriguing direction. Recent works have shown image itself can be used as a natural inter…
RaNeuS: Ray-adaptive Neural Surface Reconstruction
Yida Wang, David Joseph Tan, Nassir Navab +1
Our objective is to leverage a differentiable radiance field \eg NeRF to reconstruct detailed 3D surfaces in addition to producing the standard novel view renderings. There have be…
HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generation
Zhiying Leng, Tolga Birdal, Xiaohui Liang +1
3D shape generation from text is a fundamental task in 3D representation learning. The text-shape pairs exhibit a hierarchical structure, where a general text like ``chair" covers…
BRAVE: Broadening the visual encoding of vision-language models
Oğuzhan Fatih Kar, Alessio Tonioni, Petra Poklukar +3
Vision-language models (VLMs) are typically composed of a vision encoder, e.g. CLIP, and a language model (LM) that interprets the encoded features to solve downstream tasks. Despi…
PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations
Yang Zheng, Qingqing Zhao, Guandao Yang +8
Modeling and rendering photorealistic avatars is of crucial importance in many applications. Existing methods that build a 3D avatar from visual observations, however, struggle to…