7 citations · 7 across the 2 of their papers we have counts for
5 papers
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification
Sharath Girish, Kamal Gupta, Saurabh Singh +1
We introduce LilNetX, an end-to-end trainable technique for neural networks that enables learning models with specified accuracy-rate-computation trade-off. Prior works approach th…
One Network Doesn't Rule Them All: Moving Beyond Handcrafted Architectures in Self-Supervised Learning
Sharath Girish, Debadeepta Dey, Neel Joshi +5
The current literature on self-supervised learning (SSL) focuses on developing learning objectives to train neural networks more effectively on unlabeled data. The typical developm…
Towards Discovery and Attribution of Open-world GAN Generated Images
Sharath Girish, Saksham Suri, Saketh Rambhatla +1
With the recent progress in Generative Adversarial Networks (GANs), it is imperative for media and visual forensics to develop detectors which can identify and attribute images to…
The Lottery Ticket Hypothesis for Object Recognition
Sharath Girish, Shishira R. Maiya, Kamal Gupta +3
Recognition tasks, such as object recognition and keypoint estimation, have seen widespread adoption in recent years. Most state-of-the-art methods for these tasks use deep network…
A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections
Anil Kumar Vadathya, Sharath Girish, Kaushik Mitra
Light field presents a rich way to represent the 3D world by capturing the spatio-angular dimensions of the visual signal. However, the popular way of capturing light field (LF) vi…