3 papers
cs.CV2018
Unsupervised Feature Learning of Human Actions as Trajectories in Pose Embedding Manifold
Jogendra Nath Kundu, Maharshi Gor, Phani Krishna Uppala +1
An unsupervised human action modeling framework can provide useful pose-sequence representation, which can be utilized in a variety of pose analysis applications. In this work we p…
cs.CV2018
Ask, Acquire, and Attack: Data-free UAP Generation using Class Impressions
Konda Reddy Mopuri, Phani Krishna Uppala, R. Venkatesh Babu
Deep learning models are susceptible to input specific noise, called adversarial perturbations. Moreover, there exist input-agnostic noise, called Universal Adversarial Perturbatio…
cs.CV2018
AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation
Jogendra Nath Kundu, Phani Krishna Uppala, Anuj Pahuja +1
Supervised deep learning methods have shown promising results for the task of monocular depth estimation; but acquiring ground truth is costly, and prone to noise as well as inaccu…