6 citations · 10 across the 4 of their papers we have counts for
8 papers
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction
Moitreya Chatterjee, Narendra Ahuja, Anoop Cherian
Predicting the future frames of a video is a challenging task, in part due to the underlying stochastic real-world phenomena. Prior approaches to solve this task typically estimate…
Visual Scene Graphs for Audio Source Separation
Moitreya Chatterjee, Jonathan Le Roux, Narendra Ahuja +1
State-of-the-art approaches for visually-guided audio source separation typically assume sources that have characteristic sounds, such as musical instruments. These approaches ofte…
Unsupervised 3D Pose Estimation for Hierarchical Dance Video Recognition
Xiaodan Hu, Narendra Ahuja
Dance experts often view dance as a hierarchy of information, spanning low-level (raw images, image sequences), mid-levels (human poses and bodypart movements), and high-level (dan…
Sound2Sight: Generating Visual Dynamics from Sound and Context
Anoop Cherian, Moitreya Chatterjee, Narendra Ahuja
Learning associations across modalities is critical for robust multimodal reasoning, especially when a modality may be missing during inference. In this paper, we study this proble…
Coreset-Based Neural Network Compression
Abhimanyu Dubey, Moitreya Chatterjee, Narendra Ahuja
We propose a novel Convolutional Neural Network (CNN) compression algorithm based on coreset representations of filters. We exploit the redundancies extant in the space of CNN weig…
DeepMVS: Learning Multi-view Stereopsis
Po-Han Huang, Kevin Matzen, Johannes Kopf +2
We present DeepMVS, a deep convolutional neural network (ConvNet) for multi-view stereo reconstruction. Taking an arbitrary number of posed images as input, we first produce a set…