no code implementations • 18 Mar 2024 • Shubhra Aich, Wenshan Wang, Parv Maheshwari, Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Jason M. Gregory, John G. Rogers III, Sebastian Scherer
The limited sensing resolution of resource-constrained off-road vehicles poses significant challenges towards reliable off-road autonomy.
no code implementations • 17 Jan 2023 • Sajith Rajapaksa, Jean Marie Uwabeza Vianney, Renell Castro, Farzad Khalvati, Shubhra Aich
This paper investigates the potential usage of large text-to-image (LTI) models for the automated diagnosis of a few skin conditions with rarity or a serious lack of annotated datasets.
1 code implementation • ICCV 2023 • Shubhra Aich, Jesus Ruiz-Santaquiteria, Zhenyu Lu, Prachi Garg, K J Joseph, Alvaro Fernandez Garcia, Vineeth N Balasubramanian, Kenrick Kin, Chengde Wan, Necati Cihan Camgoz, Shugao Ma, Fernando de la Torre
Our sampling scheme outperforms SOTA methods significantly on two 3D skeleton gesture datasets, the publicly available SHREC 2017, and EgoGesture3D -- which we extract from a publicly available RGBD dataset.
no code implementations • 14 Jan 2022 • Eduardo R. Corral-Soto, Mrigank Rochan, Yannis Y. He, Shubhra Aich, Yang Liu, Liu Bingbing
We consider the setting where we have a fully-labeled data set from source domain and a target domain with a few labeled and many unlabeled examples.
no code implementations • 20 Jul 2021 • Mrigank Rochan, Shubhra Aich, Eduardo R. Corral-Soto, Amir Nabatchian, Bingbing Liu
In this paper, we focus on a less explored, but more realistic and complex problem of domain adaptation in LiDAR semantic segmentation.
1 code implementation • 1 Sep 2020 • Shubhra Aich, Jean Marie Uwabeza Vianney, Md Amirul Islam, Mannat Kaur, Bingbing Liu
In this paper, we propose a Bidirectional Attention Network (BANet), an end-to-end framework for monocular depth estimation (MDE) that addresses the limitation of effectively integrating local and global information in convolutional neural networks.
no code implementations • 9 Jan 2020 • Shubhra Aich, Ian Stavness, Yasuhiro Taniguchi, Masaki Yamazaki
In this paper, we explore the idea of weight sharing over multiple scales in convolutional networks.
no code implementations • 21 Nov 2019 • Jean Marie Uwabeza Vianney, Shubhra Aich, Bingbing Liu
In this paper, we strive for solving the ambiguities arisen by the astoundingly high density of raw PseudoLiDAR for monocular 3D object detection for autonomous driving.
no code implementations • 28 May 2018 • Shubhra Aich, Ian Stavness
This generalization capability allows GSP to avoid both patchwise cancellation and overfitting by training on small patches and inference on full-resolution images as a whole.
1 code implementation • 1 May 2018 • Shubhra Aich, William van der Kamp, Ian Stavness
In this paper, we propose an efficient architecture for semantic image segmentation using the depth-to-space (D2S) operation.
2 code implementations • 14 Mar 2018 • Shubhra Aich, Ian Stavness
Adding HR to a simple VGG front-end improves performance on all these benchmarks compared to a simple one-look baseline model and results in state-of-the-art performance for car counting.
1 code implementation • 30 Sep 2017 • Shubhra Aich, Anique Josuttes, Ilya Ovsyannikov, Keegan Strueby, Imran Ahmed, Hema Sudhakar Duddu, Curtis Pozniak, Steve Shirtliffe, Ian Stavness
In this paper, we investigate estimating emergence and biomass traits from color images and elevation maps of wheat field plots.
1 code implementation • 24 Aug 2017 • Shubhra Aich, Ian Stavness
In this paper, we investigate the problem of counting rosette leaves from an RGB image, an important task in plant phenotyping.