activity
20172026
most citedEncoding Invariances in Deep Generative Models

20 citations · 34 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2026

FMS: Unified Flow Matching for Segmentation and Synthesis of Thin Structures

Babak Asadi, Peiyang Wu, Mani Golparvar-Fard +2

Segmenting thin structures like infrastructure cracks and anatomical vessels is a task hampered by topology-sensitive geometry, high annotation costs, and poor generalization acros…

cs.CV2023

JoIN: Joint GANs Inversion for Intrinsic Image Decomposition

Viraj Shah, Svetlana Lazebnik, Julien Philip

Intrinsic Image Decomposition (IID) is a challenging inverse problem that seeks to decompose a natural image into its underlying intrinsic components such as albedo and shading. Wh…

cs.CV2023★ 5 cited

Make It So: Steering StyleGAN for Any Image Inversion and Editing

Anand Bhattad, Viraj Shah, Derek Hoiem +1

StyleGAN's disentangled style representation enables powerful image editing by manipulating the latent variables, but accurately mapping real-world images to their latent variables…

cs.CV2022

MultiStyleGAN: Multiple One-shot Image Stylizations using a Single GAN

Viraj Shah, Ayush Sarkar, Sudharsan Krishnakumar Anitha +1

Image stylization aims at applying a reference style to arbitrary input images. A common scenario is one-shot stylization, where only one example is available for each reference st…

cs.CV2022★ 7 cited

Near Perfect GAN Inversion

Qianli Feng, Viraj Shah, Raghudeep Gadde +2

To edit a real photo using Generative Adversarial Networks (GANs), we need a GAN inversion algorithm to identify the latent vector that perfectly reproduces it. Unfortunately, wher…

cs.CV2021

CloudFindr: A Deep Learning Cloud Artifact Masker for Satellite DEM Data

Kalina Borkiewicz, Viraj Shah, J. P. Naiman +3

Artifact removal is an integral component of cinematic scientific visualization, and is especially challenging with big datasets in which artifacts are difficult to define. In this…