1 code implementation • 22 Mar 2022 • Chenyun Wu, Subhransu Maji
We investigate how well CLIP understands texture in natural images described by natural language.
no code implementations • ECCV 2020 • Chenyun Wu, Mikayla Timm, Subhransu Maji
Textures in natural images can be characterized by color, shape, periodicity of elements within them, and other attributes that can be described using natural language.
1 code implementation • CVPR 2020 • Chenyun Wu, Zhe Lin, Scott Cohen, Trung Bui, Subhransu Maji
We consider the problem of segmenting image regions given a natural language phrase, and study it on a novel dataset of 77, 262 images and 345, 486 phrase-region pairs.
Ranked #4 on Referring Expression Segmentation on PhraseCut
no code implementations • 2 Jul 2019 • Tsung-Yu Lin, Mikayla Timm, Chenyun Wu, Subhransu Maji
We analyze how categories from recent FGVC challenges can be described by their textural content.
no code implementations • ICCV 2017 • Jong-Chyi Su, Chenyun Wu, Huaizu Jiang, Subhransu Maji
We collect a large dataset of such phrases by asking annotators to describe several visual differences between a pair of instances within a category.