no code implementations • 17 Sep 2024 • Aditya Humnabadkar, Arindam Sikdar, Benjamin Cave, Huaizhong Zhang, Paul Bakaki, Ardhendu Behera
We present an innovative framework for traffic dynamics analysis using High-Order Evolving Graphs, designed to improve spatio-temporal representations in autonomous driving contexts.
1 code implementation • 5 Sep 2022 • Asish Bera, Zachary Wharton, Yonghuai Liu, Nik Bessis, Ardhendu Behera
Over the past few years, a significant progress has been made in deep convolutional neural networks (CNNs)-based image recognition.
Ranked #1 on Fine-Grained Image Classification on Stanford Dogs
1 code implementation • 23 Aug 2022 • Jinkui Hao, Ting Shen, Xueli Zhu, Yonghuai Liu, Ardhendu Behera, Dan Zhang, Bang Chen, Jiang Liu, Jiong Zhang, Yitian Zhao
Automated detection of retinal structures, such as retinal vessels (RV), the foveal avascular zone (FAZ), and retinal vascular junctions (RVJ), are of great importance for understanding diseases of the eye and clinical decision-making.
no code implementations • 11 Jan 2022 • Swagat Kumar, Hayden Sampson, Ardhendu Behera
To the best of our knowledge, such a benchmarking study is not available for the above two vision-based robotics problems making it a novel contribution in the field.
1 code implementation • 23 Oct 2021 • Asish Bera, Zachary Wharton, Yonghuai Liu, Nik Bessis, Ardhendu Behera
We address this by proposing an end-to-end CNN model, which learns meaningful features linking fine-grained changes using our novel attention mechanism.
Ranked #1 on Image Classification on Caltech-256
no code implementations • 23 Oct 2021 • Zachary Wharton, Ardhendu Behera, Asish Bera
Convolutional Neural Networks (CNNs) have revolutionized the understanding of visual content.
no code implementations • 17 Jan 2021 • Zachary Wharton, Ardhendu Behera, Yonghuai Liu, Nik Bessis
Our model is named Coarse Temporal Attention Network (CTA-Net), in which coarse temporal branches are introduced in a trainable glimpse network.
1 code implementation • 17 Jan 2021 • Ardhendu Behera, Zachary Wharton, Pradeep Hewage, Asish Bera
We evaluate our approach using six state-of-the-art (SotA) backbone networks and eight benchmark datasets.
Ranked #1 on Fine-Grained Image Classification on Food-101
no code implementations • 17 Jan 2021 • Ardhendu Behera, Zachary Wharton, Morteza Ghahremani, Swagat Kumar, Nik Bessis
Affect is often expressed via non-verbal body language such as actions/gestures, which are vital indicators for human behaviors.
Facial Expression Recognition Facial Expression Recognition (FER) +2
1 code implementation • ECCV 2020 • Madhu Vankadari, Sourav Garg, Anima Majumder, Swagat Kumar, Ardhendu Behera
We propose to solve this problem by posing it as a domain adaptation problem where a network trained with day-time images is adapted to work for night-time images.
1 code implementation • 21 Aug 2020 • Morteza Ghahremani, Bernard Tiddeman, Yonghuai Liu, Ardhendu Behera
Our method extracts the deep patterns inside a 3D object via creating a dynamic link to seek the most stable patterns and at once, throws away the unstable ones.