b'Stan Sclaroff'

research

∙ 08/03/2023

DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations

Multi-label image recognition in the low-label regime is a task of great...

0 Ping Hu, et al. ∙

research

∙ 06/30/2023

Hardwiring ViT Patch Selectivity into CNNs using Patch Mixing

Vision transformers (ViTs) have significantly changed the computer visio...

0 Ariel N. Lee, et al. ∙

research

∙ 11/29/2022

Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing

Modern deep neural networks tend to be evaluated on static test sets. On...

0 Nataniel Ruiz, et al. ∙

research

∙ 04/25/2022

Temporal Relevance Analysis for Video Action Models

In this paper, we provide a deep analysis of temporal modeling for actio...

0 Quanfu Fan, et al. ∙

research

∙ 04/07/2022

Many-to-many Splatting for Efficient Video Frame Interpolation

Motion-based video frame interpolation commonly relies on optical flow t...

1 Ping Hu, et al. ∙

research

∙ 04/01/2022

A Unified Framework for Domain Adaptive Pose Estimation

While pose estimation is an important computer vision task, it requires ...

0 Donghyun Kim, et al. ∙

research

∙ 03/22/2022

A Broad Study of Pre-training for Domain Generalization and Adaptation

Deep models must learn robust and transferable representations in order ...

0 Donghyun Kim, et al. ∙

research

∙ 08/26/2021

Learning Cross-modal Contrastive Features for Video Domain Adaptation

Learning transferable and domain adaptive feature representations from v...

0 Donghyun Kim, et al. ∙

research

∙ 08/24/2021

Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density

Unsupervised domain adaptation (UDA) methods can dramatically improve ge...

0 Kuniaki Saito, et al. ∙

research

∙ 06/08/2021

Simulated Adversarial Testing of Face Recognition Models

Most machine learning models are validated and tested on fixed datasets....

0 Nataniel Ruiz, et al. ∙

research

∙ 01/12/2021

CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions

Natural Language (NL) descriptions can be the most convenient or the onl...

0 Qi Feng, et al. ∙

research

∙ 08/01/2020

Self-supervised Visual Attribute Learning for Fashion Compatibility

Many self-supervised learning (SSL) methods have been successful in lear...

6 Donghyun Kim, et al. ∙

research

∙ 07/07/2020

Real-time Semantic Segmentation with Fast Attention

In deep CNN based models for semantic segmentation, high accuracy relies...

0 Ping Hu, et al. ∙

research

∙ 06/11/2020

Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks

In this work, we develop efficient disruptions of black-box image transl...

8 Nataniel Ruiz, et al. ∙

research

∙ 04/03/2020

Temporally Distributed Networks for Fast Video Segmentation

We present TDNet, a temporally distributed network designed for fast and...

13 Ping Hu, et al. ∙

research

∙ 04/03/2020

Temporally Distributed Networks for Fast Video Semantic Segmentation

We present TDNet, a temporally distributed network designed for fast and...

1 Ping Hu, et al. ∙

research

∙ 04/01/2020

Spatio-Temporal Action Detection with Multi-Object Interaction

Spatio-temporal action detection in videos requires localizing the actio...

13 Huijuan Xu, et al. ∙

research

∙ 03/18/2020

Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels

Existing unsupervised domain adaptation methods aim to transfer knowledg...

5 Donghyun Kim, et al. ∙

research

∙ 03/13/2020

Explainable Deep Classification Models for Domain Generalization

Conventionally, AI models are thought to trade off explainability for lo...

21 Andrea Zunino, et al. ∙

research

∙ 03/03/2020

Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems

Face modification systems using deep learning have become increasingly p...

7 Nataniel Ruiz, et al. ∙

research

∙ 02/19/2020

Universal Domain Adaptation through Self Supervision

Unsupervised domain adaptation methods traditionally assume that all sou...

15 Kuniaki Saito, et al. ∙

research

∙ 02/18/2020

Multi-Task Learning from Videos via Efficient Inter-Frame Attention

Prior work in multi-task learning has mainly focused on predictions on a...

28 Donghyun Kim, et al. ∙

research

∙ 02/12/2020

Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System

In the context of building an intelligent tutoring system (ITS), which i...

9 Nataniel Ruiz, et al. ∙

research

∙ 12/23/2019

DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition

In this work, we address the problem of learning an ensemble of speciali...

27 Nuno C. Garcia, et al. ∙

research

∙ 12/04/2019

Robust Visual Object Tracking with Natural Language Region Proposal Network

Tracking with natural-language (NL) specification is a powerful new para...

28 Qi Feng, et al. ∙

research

∙ 09/08/2019

MULE: Multimodal Universal Language Embedding

Existing vision-language methods typically support two languages at a ti...

4 Donghyun Kim, et al. ∙

research

∙ 08/17/2019

Language Features Matter: Effective Language Representations for Vision-Language Tasks

Shouldn't language and vision features be treated equally in vision-lang...

4 Andrea Burns, et al. ∙

research

∙ 07/26/2019

Tell Me What to Track

In recent years, deep-learning-based visual object trackers have been st...

2 Qi Feng, et al. ∙

research

∙ 06/11/2019

Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition

Learning from a few examples is a challenging task for machine learning....

2 Ping Hu, et al. ∙

research

∙ 06/05/2019

Multi-way Encoding for Robustness

Deep models are state-of-the-art for many computer vision tasks includin...

1 Donghyun Kim, et al. ∙

research

∙ 04/13/2019

Semi-supervised Domain Adaptation via Minimax Entropy

Contemporary domain adaptation methods are very effective at aligning fe...

6 Kuniaki Saito, et al. ∙

research

∙ 12/06/2018

Guided Zoom: Questioning Network Evidence for Fine-grained Classification

We propose Guided Zoom, an approach that utilizes spatial grounding to m...

5 Sarah Adel Bargal, et al. ∙

research

∙ 11/17/2018

Open-vocabulary Phrase Detection

Most existing work that grounds natural language phrases in images start...

0 Bryan A. Plummer, et al. ∙

research

∙ 11/16/2018

Learning Where to Fixate on Foveated Images

Foveation, the ability to sequentially acquire high-acuity regions of a ...

12 Hanxiao Wang, et al. ∙

research

∙ 08/06/2018

Hashing with Binary Matrix Pursuit

We propose theoretical and empirical improvements for two-stage hashing ...

6 Fatih Cakir, et al. ∙

research

∙ 05/23/2018

Excitation Dropout: Encouraging Plasticity in Deep Neural Networks

We propose a guided dropout regularizer for deep networks based on the e...

8 Andrea Zunino, et al. ∙

research

∙ 04/15/2018

Local Descriptors Optimized for Average Precision

Extraction of local feature descriptors is a vital stage in the solution...

0 Kun He, et al. ∙

research

∙ 04/13/2018

Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning

We propose a novel method capable of retrieving clips from untrimmed vid...

0 Huijuan Xu, et al. ∙

research

∙ 03/02/2018

Hashing with Mutual Information

Binary vector embeddings enable fast nearest neighbor retrieval in large...

0 Fatih Cakir, et al. ∙

research

∙ 11/18/2017

Excitation Backprop for RNNs

Deep models are state-of-the-art for many vision tasks including video a...

0 Sarah Adel Bargal, et al. ∙

research

∙ 05/23/2017

Hashing as Tie-Aware Learning to Rank

Hashing, or learning binary embeddings of data, is frequently used in ne...

0 Kun He, et al. ∙

research

∙ 03/27/2017

MIHash: Online Hashing with Mutual Information

Learning-based hashing methods are widely used for nearest neighbor retr...

0 Fatih Cakir, et al. ∙

research

∙ 02/02/2017

Automating Image Analysis by Annotating Landmarks with Deep Neural Networks

Image and video analysis is often a crucial step in the study of animal ...

0 Mikhail Breslav, et al. ∙

research

∙ 08/01/2016

Top-down Neural Attention by Excitation Backprop

We aim to model the top-down attention of a Convolutional Neural Network...

0 Jianming Zhang, et al. ∙

research

∙ 07/26/2016

Salient Object Subitizing

We study the problem of Salient Object Subitizing, i.e. predicting the e...

0 Jianming Zhang, et al. ∙

research

∙ 12/22/2015

Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web

Recently, attempts have been made to collect millions of videos to train...

0 Shugao Ma, et al. ∙

research

∙ 11/10/2015

Online Supervised Hashing for Ever-Growing Datasets

Supervised hashing methods are widely-used for nearest neighbor search i...

0 Fatih Cakir, et al. ∙

research

∙ 06/25/2015

Generalized Majorization-Minimization

Non-convex optimization is ubiquitous in machine learning. The Majorizat...

0 Sobhan Naderi Parizi, et al. ∙

research

∙ 03/04/2015

Class Probability Estimation via Differential Geometric Regularization

We study the problem of supervised learning for both binary and multicla...

0 Qinxun Bai, et al. ∙

research

∙ 07/23/2014

Visual Word Selection without Re-Coding and Re-Pooling

The Bag-of-Words (BoW) representation is widely used in computer vision....

0 Fatih Cakir, et al. ∙

Stan Sclaroff

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