41 citations · 134 across the 24 of their papers we have counts for
5 papers · 1 filter
Multi-Tailed, Multi-Headed, Spatial Dynamic Memory refined Text-to-Image Synthesis
Amrit Diggavi Seshadri, Balaraman Ravindran
Synthesizing high-quality, realistic images from text-descriptions is a challenging task, and current methods synthesize images from text in a multi-stage manner, typically by firs…
Reinforcement Learning for Improving Object Detection
Siddharth Nayak, Balaraman Ravindran
The performance of a trained object detection neural network depends a lot on the image quality. Generally, images are pre-processed before feeding them into the neural network and…
Understanding Dynamic Scenes using Graph Convolution Networks
Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan +3
We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed b…
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks
Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan +3
Understanding on-road vehicle behaviour from a temporal sequence of sensor data is gaining in popularity. In this paper, we propose a pipeline for understanding vehicle behaviour f…
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks
Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra +1
Recently there has been a lot of work on pruning filters from deep convolutional neural networks (CNNs) with the intention of reducing computations. The key idea is to rank the fil…