Search Results for author: Bradley Green

Found 18 papers, 5 papers with code

Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation

no code implementations10 Apr 2023 Inkyu Shin, Dahun Kim, Qihang Yu, Jun Xie, Hong-Seok Kim, Bradley Green, In So Kweon, Kuk-Jin Yoon, Liang-Chieh Chen

The meta architecture of the proposed Video-kMaX consists of two components: within clip segmenter (for clip-level segmentation) and cross-clip associater (for association beyond clips).

Segmentation Video Panoptic Segmentation +1

Federated Training of Dual Encoding Models on Small Non-IID Client Datasets

no code implementations30 Sep 2022 Raviteja Vemulapalli, Warren Richard Morningstar, Philip Andrew Mansfield, Hubert Eichner, Karan Singhal, Arash Afkanpour, Bradley Green

In this work, we focus on federated training of dual encoding models on decentralized data composed of many small, non-IID (independent and identically distributed) client datasets.

Federated Learning Representation Learning

Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data

no code implementations ICCV 2021 Xuhui Jia, Kai Han, Yukun Zhu, Bradley Green

This paper studies the problem of novel category discovery on single- and multi-modal data with labels from different but relevant categories.

Contrastive Learning Representation Learning

A Flexible Framework for Discovering Novel Categories with Contrastive Learning

no code implementations1 Jan 2021 Xuhui Jia, Kai Han, Yukun Zhu, Bradley Green

This paper studies the problem of novel category discovery on single- and multi-modal data with labels from different but relevant categories.

Contrastive Learning Representation Learning

Contrastive Learning for Label Efficient Semantic Segmentation

no code implementations ICCV 2021 Xiangyun Zhao, Raviteja Vemulapalli, Philip Andrew Mansfield, Boqing Gong, Bradley Green, Lior Shapira, Ying Wu

While recent Convolutional Neural Network (CNN) based semantic segmentation approaches have achieved impressive results by using large amounts of labeled training data, their performance drops significantly as the amount of labeled data decreases.

Contrastive Learning Segmentation +1

Contrastive Learning for Label-Efficient Semantic Segmentation

no code implementations13 Dec 2020 Xiangyun Zhao, Raviteja Vemulapalli, Philip Mansfield, Boqing Gong, Bradley Green, Lior Shapira, Ying Wu

While recent Convolutional Neural Network (CNN) based semantic segmentation approaches have achieved impressive results by using large amounts of labeled training data, their performance drops significantly as the amount of labeled data decreases.

Contrastive Learning Segmentation +1

Ranking Neural Checkpoints

1 code implementation CVPR 2021 Yandong Li, Xuhui Jia, Ruoxin Sang, Yukun Zhu, Bradley Green, Liqiang Wang, Boqing Gong

This paper is concerned with ranking many pre-trained deep neural networks (DNNs), called checkpoints, for the transfer learning to a downstream task.

Transferability Transfer Learning

Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze

no code implementations15 Oct 2020 Bardia Doosti, Ching-Hui Chen, Raviteja Vemulapalli, Xuhui Jia, Yukun Zhu, Bradley Green

In this work, we focus on the task of image-based mutual gaze detection, and propose a simple and effective approach to boost the performance by using an auxiliary 3D gaze estimation task during the training phase.

Gaze Estimation Mutual Gaze

Search to Distill: Pearls are Everywhere but not the Eyes

no code implementations CVPR 2020 Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang

Standard Knowledge Distillation (KD) approaches distill the knowledge of a cumbersome teacher model into the parameters of a student model with a pre-defined architecture.

Ensemble Learning Face Recognition +3

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