no code implementations • 3 Mar 2023 • Marvin Klingner, Shubhankar Borse, Varun Ravi Kumar, Behnaz Rezaei, Venkatraman Narayanan, Senthil Yogamani, Fatih Porikli
Specifically, we propose cross-task distillation from an instance segmentation teacher (X-IS) in the PV feature extraction stage providing supervision without ambiguous error backpropagation through the view transformation.
no code implementations • CVPR 2023 • Marvin Klingner, Shubhankar Borse, Varun Ravi Kumar, Behnaz Rezaei, Venkatraman Narayanan, Senthil Yogamani, Fatih Porikli
Specifically, we propose cross-task distillation from an instance segmentation teacher (X-IS) in the PV feature extraction stage providing supervision without ambiguous error backpropagation through the view transformation.
Ranked #5 on 3D Object Detection on nuscenes Camera-Radar
no code implementations • 17 Nov 2020 • Venkatraman Narayanan, Bala Murali Manoghar, Rama Prashanth RV, Phu Pham, Aniket Bera
Amodal recognition is the ability of the system to detect occluded objects.
1 code implementation • 16 Oct 2020 • Sumanth Chennupati, Venkatraman Narayanan, Ganesh Sistu, Senthil Yogamani, Samir A Rawashdeh
Instance contours along with semantic segmentation yield a boundary aware semantic segmentation of things.
1 code implementation • 2 Mar 2020 • Venkatraman Narayanan, Bala Murali Manoghar, Vishnu Sashank Dorbala, Dinesh Manocha, Aniket Bera
Our approach predicts the perceived emotions of a pedestrian from walking gaits, which is then used for emotion-guided navigation taking into account social and proxemic constraints.
Ranked #1 on Emotion Classification on EWALK
11 code implementations • 1 Nov 2017 • Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, Dieter Fox
We conduct extensive experiments on our YCB-Video dataset and the OccludedLINEMOD dataset to show that PoseCNN is highly robust to occlusions, can handle symmetric objects, and provide accurate pose estimation using only color images as input.
Ranked #3 on 6D Pose Estimation using RGB on YCB-Video
no code implementations • 19 Oct 2015 • Venkatraman Narayanan, Maxim Likhachev
In many robotic domains such as flexible automated manufacturing or personal assistance, a fundamental perception task is that of identifying and localizing objects whose 3D models are known.