b'Larry Davis'

research

∙ 04/18/2022

Neural Space-filling Curves

We present Neural Space-filling Curves (SFCs), a data-driven approach to...

0 Hanyu Wang, et al. ∙

research

∙ 01/31/2022

Leveraging Bitstream Metadata for Fast and Accurate Video Compression Correction

Video compression is a central feature of the modern internet powering t...

0 Max Ehrlich, et al. ∙

research

∙ 10/11/2021

Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency

Synthesizing images of a person in novel poses from a single image is a ...

9 Soubhik Sanyal, et al. ∙

research

∙ 05/20/2021

More Than Just Attention: Learning Cross-Modal Attentions with Contrastive Constraints

Attention mechanisms have been widely applied to cross-modal tasks such ...

21 Yuxiao Chen, et al. ∙

research

∙ 05/16/2021

Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer

Urban material recognition in remote sensing imagery is a highly relevan...

0 Arthita Ghosh, et al. ∙

research

∙ 05/06/2021

VideoLT: Large-scale Long-tailed Video Recognition

Label distributions in real-world are oftentimes long-tailed and imbalan...

10 Xing Zhang, et al. ∙

research

∙ 04/24/2021

M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers

We present a novel architecture for 3D object detection, M3DeTR, which c...

19 Tianrui Guan, et al. ∙

research

∙ 04/02/2021

Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories

The standard way of training video models entails sampling at each itera...

0 Xitong Yang, et al. ∙

research

∙ 03/09/2021

Knowledge Evolution in Neural Networks

Deep learning relies on the availability of a large corpus of data (labe...

0 Ahmed Taha, et al. ∙

research

∙ 03/04/2021

SVMax: A Feature Embedding Regularizer

A neural network regularizer (e.g., weight decay) boosts performance by ...

0 Ahmed Taha, et al. ∙

research

∙ 12/16/2020

Responsible Disclosure of Generative Models Using Scalable Fingerprinting

Over the past six years, deep generative models have achieved a qualitat...

0 Ning Yu, et al. ∙

research

∙ 12/08/2020

The Lottery Ticket Hypothesis for Object Recognition

Recognition tasks, such as object recognition and keypoint estimation, h...

0 Sharath Girish, et al. ∙

research

∙ 11/20/2020

SLADE: A Self-Training Framework For Distance Metric Learning

Most existing distance metric learning approaches use fully labeled data...

4 Jiali Duan, et al. ∙

research

∙ 11/17/2020

Analyzing and Mitigating Compression Defects in Deep Learning

With the proliferation of deep learning methods, many computer vision pr...

1 Max Ehrlich, et al. ∙

research

∙ 07/20/2020

Hierarchical Contrastive Motion Learning for Video Action Recognition

One central question for video action recognition is how to model motion...

4 Xitong Yang, et al. ∙

research

∙ 07/19/2020

ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors

The widely adopted sequential variant of Non Maximum Suppression (or Gre...

0 Rohun Tripathi, et al. ∙

research

∙ 07/19/2020

A Generic Visualization Approach for Convolutional Neural Networks

Retrieval networks are essential for searching and indexing. Compared to...

59 Ahmed Taha, et al. ∙

research

∙ 06/25/2020

Layout Generation and Completion with Self-attention

We address the problem of layout generation for diverse domains such as ...

5 Kamal Gupta, et al. ∙

research

∙ 04/17/2020

Quantization Guided JPEG Artifact Correction

The JPEG image compression algorithm is the most popular method of image...

10 Max Ehrlich, et al. ∙

research

∙ 04/07/2020

Inclusive GAN: Improving Data and Minority Coverage in Generative Models

Generative Adversarial Networks (GANs) have brought about rapid progress...

5 Ning Yu, et al. ∙

research

∙ 10/31/2019

Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors

We present a systematic study of adversarial attacks on state-of-the-art...

73 Zuxuan Wu, et al. ∙

research

∙ 09/27/2019

A weakly supervised adaptive triplet loss for deep metric learning

We address the problem of distance metric learning in visual similarity ...

0 Xiaonan Zhao, et al. ∙

research

∙ 04/19/2019

STEP: Spatio-Temporal Progressive Learning for Video Action Detection

In this paper, we propose Spatio-TEmporal Progressive (STEP) action dete...

8 Xitong Yang, et al. ∙

research

∙ 02/07/2019

Unsupervised Data Uncertainty Learning in Visual Retrieval Systems

We introduce an unsupervised formulation to estimate heteroscedastic unc...

10 Ahmed Taha, et al. ∙

research

∙ 01/24/2019

In Defense of the Triplet Loss for Visual Recognition

We employ triplet loss as a space embedding regularizer to boost classif...

0 Ahmed Taha, et al. ∙

research

∙ 01/23/2019

Exploring Uncertainty in Conditional Multi-Modal Retrieval Systems

We cast visual retrieval as a regression problem by posing triplet loss ...

0 Ahmed Taha, et al. ∙

research

∙ 12/31/2018

Deep Residual Learning in the JPEG Transform Domain

We introduce a general method of performing Residual Network inference a...

0 Max Ehrlich, et al. ∙

research

∙ 11/26/2018

Stacked Spatio-Temporal Graph Convolutional Networks for Action Segmentation

We propose novel Stacked Spatio-Temporal Graph Convolutional Networks (S...

0 Pallabi Ghosh, et al. ∙

research

∙ 11/20/2018

Attributing Fake Images to GANs: Analyzing Fingerprints in Generated Images

Research in computer graphics has been in pursuit of realistic image gen...

12 Ning Yu, et al. ∙

research

∙ 11/20/2018

Learning GAN fingerprints towards Image Attribution

Recent advances in Generative Adversarial Networks (GANs) have shown inc...

0 Ning Yu, et al. ∙

research

∙ 06/16/2018

Two Stream Self-Supervised Learning for Action Recognition

We present a self-supervised approach using spatio-temporal signals betw...

0 Ahmed Taha, et al. ∙

research

∙ 04/17/2018

Learning to Color from Language

Automatic colorization is the process of adding color to greyscale image...

0 Varun Manjunatha, et al. ∙

research

∙ 04/13/2018

Deep Motion Boundary Detection

Motion boundary detection is a crucial yet challenging problem. Prior me...

0 Xiaoqing Yin, et al. ∙

research

∙ 03/30/2018

Class Subset Selection for Transfer Learning using Submodularity

In recent years, it is common practice to extract fully-connected layer ...

0 Varun Manjunatha, et al. ∙

research

∙ 03/14/2018

Face-MagNet: Magnifying Feature Maps to Detect Small Faces

In this paper, we introduce the Face Magnifier Network (Face-MageNet), a...

0 Pouya Samangouei, et al. ∙

research

∙ 12/22/2017

Boundary-sensitive Network for Portrait Segmentation

Compared to the general semantic segmentation problem, portrait segmenta...

0 Xianzhi Du, et al. ∙

research

∙ 08/14/2017

SSH: Single Stage Headless Face Detector

We introduce the Single Stage Headless (SSH) face detector. Unlike two s...

0 Mahyar Najibi, et al. ∙

research

∙ 11/16/2016

The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives

Visual narrative is often a combination of explicit information and judi...

0 Mohit Iyyer, et al. ∙

research

∙ 07/12/2016

Weakly Supervised Learning of Heterogeneous Concepts in Videos

Typical textual descriptions that accompany online videos are 'weak': i....

0 Sohil Shah, et al. ∙

research

∙ 02/03/2016

Learning Discriminative Features via Label Consistent Neural Network

Deep Convolutional Neural Networks (CNN) enforces supervised information...

0 Zhuolin Jiang, et al. ∙

research

∙ 07/09/2015

Learning Structured Ordinal Measures for Video based Face Recognition

This paper presents a structured ordinal measure method for video-based ...

0 Ran He, et al. ∙

Larry Davis

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