research
∙
09/02/2023
Self-Supervised Video Transformers for Isolated Sign Language Recognition
This paper presents an in-depth analysis of various self-supervision met...
share
research
∙
05/22/2023
NeRFuser: Large-Scale Scene Representation by NeRF Fusion
A practical benefit of implicit visual representations like Neural Radia...
research
∙
06/30/2020
Classification Confidence Estimation with Test-Time Data-Augmentation
Machine learning plays an increasingly significant role in many aspects ...
research
∙
03/24/2020
Deformable Style Transfer
Both geometry and texture are fundamental aspects of visual style. Exist...
research
∙
02/27/2020
Analysis of diversity-accuracy tradeoff in image captioning
We investigate the effect of different model architectures, training obj...
research
∙
08/01/2019
DIODE: A Dense Indoor and Outdoor DEpth Dataset
We introduce DIODE, a dataset that contains thousands of diverse high re...
research
∙
02/01/2019
Natural and Adversarial Error Detection using Invariance to Image Transformations
We propose an approach to distinguish between correct and incorrect imag...
research
∙
04/05/2018
Regularizing Deep Networks by Modeling and Predicting Label Structure
We construct custom regularization functions for use in supervised train...
research
∙
04/02/2018
Confidence from Invariance to Image Transformations
We develop a technique for automatically detecting the classification er...
research
∙
03/12/2018
Discriminability objective for training descriptive captions
One property that remains lacking in image captions generated by contemp...
research
∙
10/05/2017
Semantic keyword spotting by learning from images and speech
We consider the problem of representing semantic concepts in speech by l...
research
∙
08/07/2017
Training Deep Networks to be Spatially Sensitive
In many computer vision tasks, for example saliency prediction or semant...
research
∙
03/23/2017
Visually grounded learning of keyword prediction from untranscribed speech
During language acquisition, infants have the benefit of visual cues to ...
research
∙
03/11/2017
Colorization as a Proxy Task for Visual Understanding
We investigate and improve self-supervision as a drop-in replacement for...
research
∙
01/12/2017
Comprehension-guided referring expressions
We consider generation and comprehension of natural language referring e...
research
∙
12/06/2016
Diverse Sampling for Self-Supervised Learning of Semantic Segmentation
We propose an approach for learning category-level semantic segmentation...
research
∙
11/17/2016
Examining the Impact of Blur on Recognition by Convolutional Networks
State-of-the-art algorithms for many semantic visual tasks are based on ...
research
∙
09/26/2016
Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation
We study the problem of recognizing video sequences of fingerspelled let...
research
∙
05/24/2016
FractalNet: Ultra-Deep Neural Networks without Residuals
We introduce a design strategy for neural network macro-architecture bas...
research
∙
05/23/2016
Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions
A single color image can contain many cues informative towards different...
research
∙
03/22/2016
Learning Representations for Automatic Colorization
We develop a fully automatic image colorization system. Our approach lev...
research
∙
12/02/2014