44 citations · 92 across the 6 of their papers we have counts for
6 papers
Learning Continuous 3D Words for Text-to-Image Generation
Ta-Ying Cheng, Matheus Gadelha, Thibault Groueix +4
Current controls over diffusion models (e.g., through text or ControlNet) for image generation fall short in recognizing abstract, continuous attributes like illumination direction…
3DMiner: Discovering Shapes from Large-Scale Unannotated Image Datasets
Ta-Ying Cheng, Matheus Gadelha, Soren Pirk +4
We present 3DMiner -- a pipeline for mining 3D shapes from challenging large-scale unannotated image datasets. Unlike other unsupervised 3D reconstruction methods, we assume that,…
MatFormer: A Generative Model for Procedural Materials
Paul Guerrero, Miloš Hašan, Kalyan Sunkavalli +3
Procedural material graphs are a compact, parameteric, and resolution-independent representation that are a popular choice for material authoring. However, designing procedural mat…
Recovering Detail in 3D Shapes Using Disparity Maps
Marissa Ramirez de Chanlatte, Matheus Gadelha, Thibault Groueix +1
We present a fine-tuning method to improve the appearance of 3D geometries reconstructed from single images. We leverage advances in monocular depth estimation to obtain disparity…
Photo Aesthetics Ranking Network with Attributes and Content Adaptation
Shu Kong, Xiaohui Shen, Zhe Lin +2
Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis…
Salient Object Subitizing
Jianming Zhang, Shugao Ma, Mehrnoosh Sameki +6
We study the problem of Salient Object Subitizing, i.e. predicting the existence and the number of salient objects in an image using holistic cues. This task is inspired by the abi…