no code implementations • 27 Aug 2023 • Siddharth Katageri, Arkadipta De, Chaitanya Devaguptapu, VSSV Prasad, Charu Sharma, Manohar Kaul
Recently, the fundamental problem of unsupervised domain adaptation (UDA) on 3D point clouds has been motivated by a wide variety of applications in robotics, virtual reality, and scene understanding, to name a few.
no code implementations • 26 Mar 2023 • Chaitanya Devaguptapu, Samarth Sinha, K J Joseph, Vineeth N Balasubramanian, Animesh Garg
Models pre-trained on large-scale datasets are often fine-tuned to support newer tasks and datasets that arrive over time.
no code implementations • 7 Aug 2022 • Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian
generalization remains to be a key challenge for real-world machine learning systems.
1 code implementation • 30 Nov 2020 • Akshay L Chandra, Sai Vikas Desai, Chaitanya Devaguptapu, Vineeth N Balasubramanian
While recent studies have focused on evaluating the robustness of various query functions in AL, little to no attention has been given to the design of the initial labeled pool for deep active learning.
1 code implementation • 16 Jul 2020 • Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Pulkit Gopalani, Vineeth N Balasubramanian
We show that NAS, which is popular for achieving SoTA accuracy, can provide adversarial accuracy as a free add-on without any form of adversarial training.
1 code implementation • 21 May 2019 • Chaitanya Devaguptapu, Ninad Akolekar, Manuj M Sharma, Vineeth N. Balasubramanian
Can we improve detection in the thermal domain by borrowing features from rich domains like visual RGB?