activity
20162021
most citedObject Detection with a Unified Label Space from Multiple Datasets

3 citations · 6 across the 11 of their papers we have counts for

collaborators

14 papers

cs.CV2021

Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention

Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma

Binaural audio gives the listener an immersive experience and can enhance augmented and virtual reality. However, recording binaural audio requires specialized setup with a dummy h…

cs.SD2021★ 1 cited

Depth Infused Binaural Audio Generation using Hierarchical Cross-Modal Attention

Kranti Kumar Parida, Siddharth Srivastava, Neeraj Matiyali +1

Binaural audio gives the listener the feeling of being in the recording place and enhances the immersive experience if coupled with AR/VR. But the problem with binaural audio recor…

cs.CV2021

Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks

Siddharth Srivastava, Gaurav Sharma

We propose simple yet effective improvements in point representations and local neighborhood graph construction within the general framework of graph neural networks (GNNs) for 3D…

cs.CV2021

Discriminative Semantic Transitive Consistency for Cross-Modal Learning

Kranti Kumar Parida, Gaurav Sharma

Cross-modal retrieval is generally performed by projecting and aligning the data from two different modalities onto a shared representation space. This shared space often also acts…

cs.CV2020★ 3 cited

Object Detection with a Unified Label Space from Multiple Datasets

Xiangyun Zhao, Samuel Schulter, Gaurav Sharma +3

Given multiple datasets with different label spaces, the goal of this work is to train a single object detector predicting over the union of all the label spaces. The practical ben…

cs.CV2019

Coordinated Joint Multimodal Embeddings for Generalized Audio-Visual Zeroshot Classification and Retrieval of Videos

Kranti Kumar Parida, Neeraj Matiyali, Tanaya Guha +1

We present an audio-visual multimodal approach for the task of zeroshot learning (ZSL) for classification and retrieval of videos. ZSL has been studied extensively in the recent pa…

cs.CV2019

Video Person Re-Identification using Learned Clip Similarity Aggregation

Neeraj Matiyali, Gaurav Sharma

We address the challenging task of video-based person re-identification. Recent works have shown that splitting the video sequences into clips and then aggregating clip based simil…

cs.CV2019

Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles

Siddharth Srivastava, Frederic Jurie, Gaurav Sharma

We address the problem of 3D object detection from 2D monocular images in autonomous driving scenarios. We propose to lift the 2D images to 3D representations using learned neural…

cs.CV2018

Zero-Shot Object Detection

Ankan Bansal, Karan Sikka, Gaurav Sharma +2

We introduce and tackle the problem of zero-shot object detection (ZSD), which aims to detect object classes which are not observed during training. We work with a challenging set…

cs.CV2018★ 1 cited

Unsupervised Learning of Face Representations

Samyak Datta, Gaurav Sharma, C. V. Jawahar

We present an approach for unsupervised training of CNNs in order to learn discriminative face representations. We mine supervised training data by noting that multiple faces in th…

cs.MM2017

Multichannel Attention Network for Analyzing Visual Behavior in Public Speaking

Rahul Sharma, Tanaya Guha, Gaurav Sharma

Public speaking is an important aspect of human communication and interaction. The majority of computational work on public speaking concentrates on analyzing the spoken content, a…

cs.CV2017

Large Scale Novel Object Discovery in 3D

Siddharth Srivastava, Gaurav Sharma, Brejesh Lall

We present a method for discovering never-seen-before objects in 3D point clouds obtained from sensors like Microsoft Kinect. We generate supervoxels directly from the point cloud…

cs.CV2016★ 1 cited

AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos

Amlan Kar, Nishant Rai, Karan Sikka +1

We propose a novel method for temporally pooling frames in a video for the task of human action recognition. The method is motivated by the observation that there are only a small…

cs.CV2016

LOMo: Latent Ordinal Model for Facial Analysis in Videos

Karan Sikka, Gaurav Sharma, Marian Bartlett

We study the problem of facial analysis in videos. We propose a novel weakly supervised learning method that models the video event (expression, pain etc.) as a sequence of automat…