172 citations · 1.2k across the 80 of their papers we have counts for
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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…
BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN
Jogendra Nath Kundu, Maharshi Gor, R. Venkatesh Babu
Human motion prediction model has applications in various fields of computer vision. Without taking into account the inherent stochasticity in the prediction of future pose dynamic…
CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision
Navaneet K L, Priyanka Mandikal, Mayank Agarwal +1
Knowledge of 3D properties of objects is a necessity in order to build effective computer vision systems. However, lack of large scale 3D datasets can be a major constraint for dat…
3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image
Priyanka Mandikal, Navaneet K L, R. Venkatesh Babu
We propose a mechanism to reconstruct part annotated 3D point clouds of objects given just a single input image. We demonstrate that jointly training for both reconstruction and se…
Object Pose Estimation from Monocular Image using Multi-View Keypoint Correspondence
Jogendra Nath Kundu, Rahul M. V., Aditya Ganeshan +1
Understanding the geometry and pose of objects in 2D images is a fundamental necessity for a wide range of real world applications. Driven by deep neural networks, recent methods h…
Gray-box Adversarial Training
Vivek B. S., Konda Reddy Mopuri, R. Venkatesh Babu
Adversarial samples are perturbed inputs crafted to mislead the machine learning systems. A training mechanism, called adversarial training, which presents adversarial samples alon…
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…
iSPA-Net: Iterative Semantic Pose Alignment Network
Jogendra Nath Kundu, Aditya Ganeshan, Rahul M. V. +2
Understanding and extracting 3D information of objects from monocular 2D images is a fundamental problem in computer vision. In the task of 3D object pose estimation, recent data d…
Top-Down Feedback for Crowd Counting Convolutional Neural Network
Deepak Babu Sam, R. Venkatesh Babu
Counting people in dense crowds is a demanding task even for humans. This is primarily due to the large variability in appearance of people. Often people are only seen as a bunch o…
Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN
Deepak Babu Sam, Neeraj N Sajjan, R. Venkatesh Babu
Automated counting of people in crowd images is a challenging task. The major difficulty stems from the large diversity in the way people appear in crowds. In fact, features availa…
3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image
Priyanka Mandikal, K L Navaneet, Mayank Agarwal +1
3D reconstruction from single view images is an ill-posed problem. Inferring the hidden regions from self-occluded images is both challenging and ambiguous. We propose a two-pronge…
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…
Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations
Konda Reddy Mopuri, Aditya Ganeshan, R. Venkatesh Babu
Machine learning models are susceptible to adversarial perturbations: small changes to input that can cause large changes in output. It is also demonstrated that there exist input-…