activity
20172021
most citedMulti-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras

1 citations · 1 across the 3 of their papers we have counts for

collaborators

9 papers

cs.CV2021

In Defense of Scene Graphs for Image Captioning

Kien Nguyen, Subarna Tripathi, Bang Du +2

The mainstream image captioning models rely on Convolutional Neural Network (CNN) image features to generate captions via recurrent models. Recently, image scene graphs have been u…

cs.CV2020

Compact Graph Architecture for Speech Emotion Recognition

A. Shirian, T. Guha

We propose a deep graph approach to address the task of speech emotion recognition. A compact, efficient and scalable way to represent data is in the form of graphs. Following the…

cs.CV2020

Dynamic Character Graph via Online Face Clustering for Movie Analysis

Prakhar Kulshreshtha, Tanaya Guha

An effective approach to automated movie content analysis involves building a network (graph) of its characters. Existing work usually builds a static character graph to summarize…

cs.CV2020

Ensemble Network for Ranking Images Based on Visual Appeal

Sachin Singh, Victor Sanchez, Tanaya Guha

We propose a computational framework for ranking images (group photos in particular) taken at the same event within a short time span. The ranking is expected to correspond with hu…

cs.CV20201 cited

Multi-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras

Olly Styles, Tanaya Guha, Victor Sanchez +1

We introduce the task of multi-camera trajectory forecasting (MCTF), where the future trajectory of an object is predicted in a network of cameras. Prior works consider forecasting…

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…