385 citations · 1.5k across the 36 of their papers we have counts for
5 papers · 2 filters
Content-Based Search for Deep Generative Models
Daohan Lu, Sheng-Yu Wang, Nupur Kumari +4
The growing proliferation of customized and pretrained generative models has made it infeasible for a user to be fully cognizant of every model in existence. To address this need,…
Rewriting Geometric Rules of a GAN
Sheng-Yu Wang, David Bau, Jun-Yan Zhu
Deep generative models make visual content creation more accessible to novice users by automating the synthesis of diverse, realistic content based on a collected dataset. However,…
Local Relighting of Real Scenes
Audrey Cui, Ali Jahanian, Agata Lapedriza +4
We introduce the task of local relighting, which changes a photograph of a scene by switching on and off the light sources that are visible within the image. This new task differs…
Disentangling visual and written concepts in CLIP
Joanna Materzynska, Antonio Torralba, David Bau
The CLIP network measures the similarity between natural text and images; in this work, we investigate the entanglement of the representation of word images and natural images in i…
Natural Language Descriptions of Deep Visual Features
Evan Hernandez, Sarah Schwettmann, David Bau +3
Some neurons in deep networks specialize in recognizing highly specific perceptual, structural, or semantic features of inputs. In computer vision, techniques exist for identifying…