no code implementations • 2 Oct 2023 • Viswesh N, Kaushal Jadhav, Avi Amalanshu, Bratin Mondal, Sabaris Waran, Om Sadhwani, Apoorv Kumar, Debashish Chakravarty
The following work is a reproducibility report for CLRNet: Cross Layer Refinement Network for Lane Detection.
no code implementations • 19 Aug 2022 • Rohit Ranjan, Himadri Bhakta, Animesh Jha, Parv Maheshwari, Debashish Chakravarty
This report covers our reproduction effort of the paper 'Differentiable Spatial Planning using Transformers' by Chaplot et al. .
1 code implementation • 18 Aug 2022 • Roopsa Sen, Sidharth Sinha, Parv Maheshwari, Animesh Jha, Debashish Chakravarty
The following paper is a reproducibility report for "Social NCE: Contrastive Learning of Socially-aware Motion Representations" {\cite{liu2020snce}} published in ICCV 2021 as part of the ML Reproducibility Challenge 2021.
2 code implementations • 16 Jul 2022 • Shreya Bhatt, Aayush Jain, Parv Maheshwari, Animesh Jha, Debashish Chakravarty
The following paper is a reproducibility report for "Path Planning using Neural A* Search" published in ICML2 2021 as part of the ML Reproducibility Challenge 2021.
1 code implementation • 30 Apr 2021 • Arnesh Kumar Issar, Kirtan Mali, Aryan Mehta, Karan Uppal, Saurabh Mishra, Debashish Chakravarty
The following paper is a reproducibility report for "FDA: Fourier Domain Adaptation for Semantic Segmentation" published in the CVPR 2020 as part of the ML Reproducibility Challenge 2020.
no code implementations • 18 Nov 2016 • Vikram Mohanty, Shubh Agrawal, Shaswat Datta, Arna Ghosh, Vishnu Dutt Sharma, Debashish Chakravarty
Deep Learning based techniques have been adopted with precision to solve a lot of standard computer vision problems, some of which are image classification, object detection and segmentation.