activity
20172022
most citedNatural and Adversarial Error Detection using Invariance to Image Transformations

14 citations · 54 across the 8 of their papers we have counts for

collaborators

20 papers

cs.CV20225 cited

Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation

Haochen Wang, Xiaodan Du, Jiahao Li +2

A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through…

cs.CV20221 cited

Text-Free Learning of a Natural Language Interface for Pretrained Face Generators

Xiaodan Du, Raymond A. Yeh, Nicholas Kolkin +2

We propose Fast text2StyleGAN, a natural language interface that adapts pre-trained GANs for text-guided human face synthesis. Leveraging the recent advances in Contrastive Languag…

cs.CV20208 cited

Classification Confidence Estimation with Test-Time Data-Augmentation

Yuval Bahat, Gregory Shakhnarovich

Machine learning plays an increasingly significant role in many aspects of our lives (including medicine, transportation, security, justice and other domains), making the potential…

cs.CV20204 cited

Detection and Description of Change in Visual Streams

Davis Gilton, Ruotian Luo, Rebecca Willett +1

This paper presents a framework for the analysis of changes in visual streams: ordered sequences of images, possibly separated by significant time gaps. We propose a new approach t…

cs.CV2020

Pixel Consensus Voting for Panoptic Segmentation

Haochen Wang, Ruotian Luo, Michael Maire +1

The core of our approach, Pixel Consensus Voting, is a framework for instance segmentation based on the Generalized Hough transform. Pixels cast discretized, probabilistic votes fo…

cs.CV2020

Space-Time-Aware Multi-Resolution Video Enhancement

Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We consider the problem of space-time super-resolution (ST-SR): increasing spatial resolution of video frames and simultaneously interpolating frames to increase the frame rate. Mo…