37 citations · 209 across the 24 of their papers we have counts for
14 papers · 1 filter
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning
Vinay K Verma, Nikhil Mehta, Kevin J Liang +2
Zero-shot learning (ZSL) is a promising approach to generalizing a model to categories unseen during training by leveraging class attributes, but challenges remain. Recently, metho…
Pseudo-label Correction and Learning For Semi-Supervised Object Detection
Yulin He, Wei Chen, Ke Liang +3
Pseudo-Labeling has emerged as a simple yet effective technique for semi-supervised object detection (SSOD). However, the inevitable noise problem in pseudo-labels significantly de…
EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset
Hao Tang, Kevin Liang, Matt Feiszli +1
Visual object tracking is a key component to many egocentric vision problems. However, the full spectrum of challenges of egocentric tracking faced by an embodied AI is underrepres…
Task Grouping for Multilingual Text Recognition
Jing Huang, Kevin J Liang, Rama Kovvuri +1
Most existing OCR methods focus on alphanumeric characters due to the popularity of English and numbers, as well as their corresponding datasets. On extending the characters to mor…
GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction
Samrudhdhi B Rangrej, Kevin J Liang, Tal Hassner +1
Many online action prediction models observe complete frames to locate and attend to informative subregions in the frames called glimpses and recognize an ongoing action based on g…
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection
Li Yin, Juan M Perez-Rua, Kevin J Liang
We study the challenging incremental few-shot object detection (iFSD) setting. Recently, hypernetwork-based approaches have been studied in the context of continuous and finetune-f…
Few-shot Learning with Noisy Labels
Kevin J Liang, Samrudhdhi B. Rangrej, Vladan Petrovic +1
Few-shot learning (FSL) methods typically assume clean support sets with accurately labeled samples when training on novel classes. This assumption can often be unrealistic: suppor…
Extending One-Stage Detection with Open-World Proposals
Sachin Konan, Kevin J Liang, Li Yin
In many applications, such as autonomous driving, hand manipulation, or robot navigation, object detection methods must be able to detect objects unseen in the training set. Open W…
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Weituo Hao, Mostafa El-Khamy, Jungwon Lee +4
Federated learning has emerged as an important distributed learning paradigm, where a server aggregates a global model from many client-trained models while having no access to the…
A Multiplexed Network for End-to-End, Multilingual OCR
Jing Huang, Guan Pang, Rama Kovvuri +5
Recent advances in OCR have shown that an end-to-end (E2E) training pipeline that includes both detection and recognition leads to the best results. However, many existing methods…
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning
Vinay Kumar Verma, Kevin Liang, Nikhil Mehta +1
Zero-shot learning (ZSL) has been shown to be a promising approach to generalizing a model to categories unseen during training by leveraging class attributes, but challenges still…
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images
John B. Sigman, Gregory P. Spell, Kevin J Liang +1
Recently, progress has been made in the supervised training of Convolutional Object Detectors (e.g. Faster R-CNN) for threat recognition in carry-on luggage using X-ray images. Thi…
Object Detection as a Positive-Unlabeled Problem
Yuewei Yang, Kevin J Liang, Lawrence Carin
As with other deep learning methods, label quality is important for learning modern convolutional object detectors. However, the potentially large number and wide diversity of obje…
Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection
Kevin J Liang, John B. Sigman, Gregory P. Spell +5
For the safety of the traveling public, the Transportation Security Administration (TSA) operates security checkpoints at airports in the United States, seeking to keep dangerous i…