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20152025
most citedExploring Visual Prompts for Adapting Large-Scale Models

107 citations · 165 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.CV2022

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…

cs.CV2022★ 107 cited

Exploring Visual Prompts for Adapting Large-Scale Models

Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan +1

We investigate the efficacy of visual prompting to adapt large-scale models in vision. Following the recent approach from prompt tuning and adversarial reprogramming, we learn a si…

cs.CV2021★ 6 cited

Generative Models as a Data Source for Multiview Representation Learning

Ali Jahanian, Xavier Puig, Yonglong Tian +1

Generative models are now capable of producing highly realistic images that look nearly indistinguishable from the data on which they are trained. This raises the question: if we h…

cs.CV2021★ 10 cited

Paint by Word

Alex Andonian, Sabrina Osmany, Audrey Cui +4

We investigate the problem of zero-shot semantic image painting. Instead of painting modifications into an image using only concrete colors or a finite set of semantic concepts, we…

cs.CV2020★ 2 cited

Instance Semantic Segmentation Benefits from Generative Adversarial Networks

Quang H. Le, Kamal Youcef-Toumi, Dzmitry Tsetserukou +1

In design of instance segmentation networks that reconstruct masks, segmentation is often taken as its literal definition -- assigning each pixel a label. This has led to thinking…

cs.CV2019★ 37 cited

On the "steerability" of generative adversarial networks

Ali Jahanian, Lucy Chai, Phillip Isola

An open secret in contemporary machine learning is that many models work beautifully on standard benchmarks but fail to generalize outside the lab. This has been attributed to bias…