Search Results for author: Venkatraman Narayanan

Found 7 papers, 3 papers with code

X$^3$KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection

no code implementations3 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.

3D Object Detection Instance Segmentation +3

X3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection

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.

3D Object Detection Instance Segmentation +3

ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot Navigation

1 code implementation2 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.

Emotion Classification Emotion Recognition +3

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

11 code implementations1 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.

6D Pose Estimation 6D Pose Estimation using RGB +2

PERCH: Perception via Search for Multi-Object Recognition and Localization

no code implementations19 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.

Object Recognition Scene Generation

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