27 citations · 45 across the 6 of their papers we have counts for
7 papers
Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient Distillation
Sumanth Chennupati, Mohammad Mahdi Kamani, Zhongwei Cheng +1
Knowledge Distillation is becoming one of the primary trends among neural network compression algorithms to improve the generalization performance of a smaller student model with g…
Learning Panoptic Segmentation from Instance Contours
Sumanth Chennupati, Venkatraman Narayanan, Ganesh Sistu +2
Panoptic Segmentation aims to provide an understanding of background (stuff) and instances of objects (things) at a pixel level. It combines the separate tasks of semantic segmenta…
Adaptive Hierarchical Decomposition of Large Deep Networks
Sumanth Chennupati, Sai Nooka, Shagan Sah +1
Deep learning has recently demonstrated its ability to rival the human brain for visual object recognition. As datasets get larger, a natural question to ask is if existing deep le…
FisheyeMultiNet: Real-time Multi-task Learning Architecture for Surround-view Automated Parking System
Pullarao Maddu, Wayne Doherty, Ganesh Sistu +7
Automated Parking is a low speed manoeuvring scenario which is quite unstructured and complex, requiring full 360° near-field sensing around the vehicle. In this paper, we discuss…
MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning
Sumanth Chennupati, Ganesh Sistu, Senthil Yogamani +1
Multi-task learning is commonly used in autonomous driving for solving various visual perception tasks. It offers significant benefits in terms of both performance and computationa…
AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving
Sumanth Chennupati, Ganesh Sistu, Senthil Yogamani +1
Decision making in automated driving is highly specific to the environment and thus semantic segmentation plays a key role in recognizing the objects in the environment around the…