research
∙
10/24/2022
GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction
Many online action prediction models observe complete frames to locate a...
share
research
∙
10/13/2022
Task Grouping for Multilingual Text Recognition
Most existing OCR methods focus on alphanumeric characters due to the po...
research
∙
04/12/2022
Few-shot Learning with Noisy Labels
Few-shot learning (FSL) methods typically assume clean support sets with...
research
∙
03/25/2022
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection
We study the challenging incremental few-shot object detection (iFSD) se...
research
∙
01/07/2022
Extending One-Stage Detection with Open-World Proposals
In many applications, such as autonomous driving, hand manipulation, or ...
research
∙
04/27/2021
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Federated learning has emerged as an important distributed learning para...
research
∙
03/29/2021
A Multiplexed Network for End-to-End, Multilingual OCR
Recent advances in OCR have shown that an end-to-end (E2E) training pipe...
research
∙
03/25/2021
Efficient Feature Transformations for Discriminative and Generative Continual Learning
As neural networks are increasingly being applied to real-world applicat...
research
∙
03/17/2021
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?
We design blackbox transfer-based targeted adversarial attacks for an en...
research
∙
11/01/2020
MixKD: Towards Efficient Distillation of Large-scale Language Models
Large-scale language models have recently demonstrated impressive empiri...
research
∙
10/02/2020
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images
Recently, progress has been made in the supervised training of Convoluti...
research
∙
08/13/2020
WAFFLe: Weight Anonymized Factorization for Federated Learning
In domains where data are sensitive or private, there is great value in ...
research
∙
04/29/2020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
We consider the blackbox transfer-based targeted adversarial attack thre...
research
∙
04/27/2020
Transferable Perturbations of Deep Feature Distributions
Almost all current adversarial attacks of CNN classifiers rely on inform...
research
∙
04/21/2020
Bayesian Nonparametric Weight Factorization for Continual Learning
Naively trained neural networks tend to experience catastrophic forgetti...
research
∙
02/11/2020
Object Detection as a Positive-Unlabeled Problem
As with other deep learning methods, label quality is important for lear...
research
∙
12/13/2019
Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection
For the safety of the traveling public, the Transportation Security Admi...
research
∙
10/09/2019
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
We investigate time-dependent data analysis from the perspective of recu...
research
∙
11/27/2018
