no code implementations • 21 Sep 2023 • Thanh Nguyen, Trung Pham, Chaoning Zhang, Tung Luu, Thang Vu, Chang D. Yoo
Self-supervised learning (SSL) has gained remarkable success, for which contrastive learning (CL) plays a key role.
no code implementations • 5 Apr 2023 • Yang Zheng, Oles Andrienko, Yonglei Zhao, Minwoo Park, Trung Pham
We develop a novel Deformable Polar Polygon Object Detection method (DPPD) to detect objects in polygon shapes.
no code implementations • 23 Mar 2023 • Trung Pham, Mehran Maghoumi, Wanli Jiang, Bala Siva Sashank Jujjavarapu, Mehdi Sajjadi, Xin Liu, Hsuan-Chu Lin, Bor-Jeng Chen, Giang Truong, Chao Fang, Junghyun Kwon, Minwoo Park
Achieving robust and real-time 3D perception is fundamental for autonomous vehicles.
no code implementations • 11 Aug 2022 • Trung Pham, Chaoning Zhang, Axi Niu, Kang Zhang, Chang D. Yoo
Exponential Moving Average (EMA or momentum) is widely used in modern self-supervised learning (SSL) approaches, such as MoCo, for enhancing performance.
no code implementations • 15 Mar 2021 • Thanh Nguyen, Tung Luu, Trung Pham, Sanzhar Rakhimkul, Chang D. Yoo
Model agnostic meta-learning (MAML) is a popular state-of-the-art meta-learning algorithm that provides good weight initialization of a model given a variety of learning tasks.
no code implementations • CVPR 2020 • Junyeong Kim, Minuk Ma, Trung Pham, Kyung-Su Kim, Chang D. Yoo
To this end, MSAN is based on (1) the moment proposal network (MPN) that attempts to locate the most appropriate temporal moment from each of the modalities, and also on (2) the heterogeneous reasoning network (HRN) that predicts the answer using an attention mechanism on both modalities.
no code implementations • ECCV 2018 • Kejie Li, Trung Pham, Huangying Zhan, Ian Reid
Given a single image at an arbitrary viewpoint, a CNN predicts multiple surfaces, each in a canonical location relative to the object.
no code implementations • ECCV 2018 • Trung Pham, Vijay Kumar B G, Thanh-Toan Do, Gustavo Carneiro, Ian Reid
In this paper, we present a novel open-set semantic instance segmentation approach capable of segmenting all known and unknown object classes in images, based on the output of an object detector trained on known object classes.
no code implementations • 24 Apr 2018 • Mehdi Hosseinzadeh, Yasir Latif, Trung Pham, Niko Suenderhauf, Ian Reid
Simultaneous Localization And Mapping (SLAM) is a fundamental problem in mobile robotics.
no code implementations • 28 Feb 2018 • Thanh-Toan Do, Ming Cai, Trung Pham, Ian Reid
Detecting objects and their 6D poses from only RGB images is an important task for many robotic applications.
no code implementations • 21 Feb 2018 • Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le Tan, Trung Pham, Huu Le, Ngai-Man Cheung, Ian Reid
However, training deep hashing networks for the task is challenging due to the binary constraints on the hash codes, the similarity preserving property, and the requirement for a vast amount of labelled images.
1 code implementation • NeurIPS 2017 • Toan Tran, Trung Pham, Gustavo Carneiro, Lyle Palmer, Ian Reid
Data augmentation is an essential part of the training process applied to deep learning models.
no code implementations • 21 Sep 2017 • Trung Pham, Thanh-Toan Do, Niko Sünderhauf, Ian Reid
This paper presents SceneCut, a novel approach to jointly discover previously unseen objects and non-object surfaces using a single RGB-D image.
1 code implementation • 17 Sep 2016 • Jürgen Leitner, Adam W. Tow, Jake E. Dean, Niko Suenderhauf, Joseph W. Durham, Matthew Cooper, Markus Eich, Christopher Lehnert, Ruben Mangels, Christopher Mccool, Peter Kujala, Lachlan Nicholson, Trung Pham, James Sergeant, Liao Wu, Fangyi Zhang, Ben Upcroft, Peter Corke
We present a new physical benchmark challenge for robotic picking: the ACRV Picking Benchmark (APB).