27 citations · 28 across the 3 of their papers we have counts for
4 papers
RMOPP: Robust Multi-Objective Post-Processing for Effective Object Detection
Mayuresh Savargaonkar, Abdallah Chehade, Samir Rawashdeh
Over the last few decades, many architectures have been developed that harness the power of neural networks to detect objects in near real-time. Training such systems requires subs…
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…
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…