15 citations · 51 across the 13 of their papers we have counts for
13 papers
Multi-axis Analysis of Image Manipulation Localization
Keanu Nichols, Divya Appapogu, Giscard Biamby +3
Advanced image editing software enables easy creation of highly convincing image manipulations, which has been made even more accessible in recent years due to advances in generati…
SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models
Arijit Ray, Jiafei Duan, Ellis Brown +9
Reasoning about motion and space is a fundamental cognitive capability that is required by multiple real-world applications. While many studies highlight that large multimodal lang…
Learning to Compose SuperWeights for Neural Parameter Allocation Search
Piotr Teterwak, Soren Nelson, Nikoli Dryden +3
Neural parameter allocation search (NPAS) automates parameter sharing by obtaining weights for a network given an arbitrary, fixed parameter budget. Prior work has two major drawba…
Lasagna: Layered Score Distillation for Disentangled Object Relighting
Dina Bashkirova, Arijit Ray, Rupayan Mallick +4
Professional artists, photographers, and other visual content creators use object relighting to establish their photo's desired effect. Unfortunately, manual tools that allow relig…
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting
Dina Bashkirova, Samarth Mishra, Diala Lteif +16
Label-efficient and reliable semantic segmentation is essential for many real-life applications, especially for industrial settings with high visual diversity, such as waste sortin…
MaskSketch: Unpaired Structure-guided Masked Image Generation
Dina Bashkirova, Jose Lezama, Kihyuk Sohn +2
Recent conditional image generation methods produce images of remarkable diversity, fidelity and realism. However, the majority of these methods allow conditioning only on labels o…
Disentangled Unsupervised Image Translation via Restricted Information Flow
Ben Usman, Dina Bashkirova, Kate Saenko
Unsupervised image-to-image translation methods aim to map images from one domain into plausible examples from another domain while preserving structures shared across two domains.…
VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data
Dina Bashkirova, Dan Hendrycks, Donghyun Kim +5
Progress in machine learning is typically measured by training and testing a model on the same distribution of data, i.e., the same domain. This over-estimates future accuracy on o…
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks
Andrey Zhmoginov, Dina Bashkirova, Mark Sandler
Conditional computation and modular networks have been recently proposed for multitask learning and other problems as a way to decompose problem solving into multiple reusable comp…
ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes
Dina Bashkirova, Mohamed Abdelfattah, Ziliang Zhu +7
Less than 35% of recyclable waste is being actually recycled in the US, which leads to increased soil and sea pollution and is one of the major concerns of environmental researcher…
Evaluation of Correctness in Unsupervised Many-to-Many Image Translation
Dina Bashkirova, Ben Usman, Kate Saenko
Given an input image from a source domain and a guidance image from a target domain, unsupervised many-to-many image-to-image (UMMI2I) translation methods seek to generate a plausi…
Adversarial Self-Defense for Cycle-Consistent GANs
Dina Bashkirova, Ben Usman, Kate Saenko
The goal of unsupervised image-to-image translation is to map images from one domain to another without the ground truth correspondence between the two domains. State-of-art method…
Unsupervised Video-to-Video Translation
Dina Bashkirova, Ben Usman, Kate Saenko
Unsupervised image-to-image translation is a recently proposed task of translating an image to a different style or domain given only unpaired image examples at training time. In t…