Search Results for author: Ravi Kiran Sarvadevabhatla

Found 25 papers, 16 papers with code

BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation

1 code implementation21 Aug 2021 Abhishek Trivedi, Ravi Kiran Sarvadevabhatla

Precise boundary annotations of image regions can be crucial for downstream applications which rely on region-class semantics.

Wisdom of (Binned) Crowds: A Bayesian Stratification Paradigm for Crowd Counting

1 code implementation19 Aug 2021 Sravya Vardhani Shivapuja, Mansi Pradeep Khamkar, Divij Bajaj, Ganesh Ramakrishnan, Ravi Kiran Sarvadevabhatla

We analyze the performance of representative crowd counting approaches across standard datasets at per strata level and in aggregate.

Crowd Counting

Hear Me Out: Fusional Approaches for Audio Augmented Temporal Action Localization

1 code implementation27 Jun 2021 Anurag Bagchi, Jazib Mahmood, Dolton Fernandes, Ravi Kiran Sarvadevabhatla

State of the art architectures for untrimmed video Temporal Action Localization (TAL) have only considered RGB and Flow modalities, leaving the information-rich audio modality totally unexploited.

Action Recognition

RackLay: Multi-Layer Layout Estimation for Warehouse Racks

1 code implementation16 Mar 2021 Meher Shashwat Nigam, Avinash Prabhu, Anurag Sahu, Puru Gupta, Tanvi Karandikar, N. Sai Shankar, Ravi Kiran Sarvadevabhatla, K. Madhava Krishna

Given a monocular colour image of a warehouse rack, we aim to predict the bird's-eye view layout for each shelf in the rack, which we term as multi-layer layout prediction.

NTU-X: An Enhanced Large-scale Dataset for Improving Pose-based Recognition of Subtle Human Actions

1 code implementation27 Jan 2021 Neel Trivedi, Anirudh Thatipelli, Ravi Kiran Sarvadevabhatla

The lack of fine-grained joints (facial joints, hand fingers) is a fundamental performance bottleneck for state of the art skeleton action recognition models.

Action Recognition Skeleton Based Action Recognition

Early Bird: Loop Closures from Opposing Viewpoints for Perceptually-Aliased Indoor Environments

no code implementations3 Oct 2020 Satyajit Tourani, Dhagash Desai, Udit Singh Parihar, Sourav Garg, Ravi Kiran Sarvadevabhatla, Michael Milford, K. Madhava Krishna

In particular, our integration of VPR with SLAM by leveraging the robustness of deep-learned features and our homography-based extreme viewpoint invariance significantly boosts the performance of VPR, feature correspondence, and pose graph submodules of the SLAM pipeline.

Visual Place Recognition

Quo Vadis, Skeleton Action Recognition ?

1 code implementation4 Jul 2020 Pranay Gupta, Anirudh Thatipelli, Aditya Aggarwal, Shubh Maheshwari, Neel Trivedi, Sourav Das, Ravi Kiran Sarvadevabhatla

To study skeleton-action recognition in the wild, we introduce Skeletics-152, a curated and 3-D pose-annotated subset of RGB videos sourced from Kinetics-700, a large-scale action dataset.

Action Recognition Skeleton Based Action Recognition

OPAL-Net: A Generative Model for Part-based Object Layout Generation

no code implementations30 May 2020 Rishabh Baghel, Ravi Kiran Sarvadevabhatla

We propose OPAL-Net, a novel hierarchical architecture for part-based layout generation of objects from multiple categories using a single unified model.

Topological Mapping for Manhattan-like Repetitive Environments

1 code implementation16 Feb 2020 Sai Shubodh Puligilla, Satyajit Tourani, Tushar Vaidya, Udit Singh Parihar, Ravi Kiran Sarvadevabhatla, K. Madhava Krishna

At the intermediate level, the map is represented as a Manhattan Graph where the nodes and edges are characterized by Manhattan properties and as a Pose Graph at the lower-most level of detail.

Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic Manuscripts

1 code implementation15 Dec 2019 Abhishek Prusty, Sowmya Aitha, Abhishek Trivedi, Ravi Kiran Sarvadevabhatla

To address this deficiency, we introduce Indiscapes, the first ever dataset with multi-regional layout annotations for historical Indic manuscripts.

Instance Segmentation Optical Character Recognition +1

Operator-in-the-Loop Deep Sequential Multi-camera Feature Fusion for Person Re-identification

no code implementations19 Jul 2018 K L Navaneet, Ravi Kiran Sarvadevabhatla, Shashank Shekhar, R. Venkatesh Babu, Anirban Chakraborty

Therefore, target identifications by operator in a subset of cameras cannot be utilized to improve ranking of the target in remaining set of network cameras.

Person Re-Identification

Game of Sketches: Deep Recurrent Models of Pictionary-style Word Guessing

1 code implementation29 Jan 2018 Ravi Kiran Sarvadevabhatla, Shiv Surya, Trisha Mittal, Venkatesh Babu Radhakrishnan

Similarly, performance on multi-disciplinary tasks such as Visual Question Answering (VQA) is considered a marker for gauging progress in Computer Vision.

Question Answering Visual Question Answering

DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data

2 code implementations CVPR 2017 Swaminathan Gurumurthy, Ravi Kiran Sarvadevabhatla, Venkatesh Babu Radhakrishnan

A class of recent approaches for generating images, called Generative Adversarial Networks (GAN), have been used to generate impressively realistic images of objects, bedrooms, handwritten digits and a variety of other image modalities.

Image Generation

Object category understanding via eye fixations on freehand sketches

no code implementations20 Mar 2017 Ravi Kiran Sarvadevabhatla, Sudharshan Suresh, R. Venkatesh Babu

In this paper, we analyze the results of a free-viewing gaze fixation study conducted on 3904 freehand sketches distributed across 160 object categories.

'Part'ly first among equals: Semantic part-based benchmarking for state-of-the-art object recognition systems

no code implementations23 Nov 2016 Ravi Kiran Sarvadevabhatla, Shanthakumar Venkatraman, R. Venkatesh Babu

Our results show that the proposed benchmarking procedure enables additional differentiation among state-of-the-art object classifiers in terms of their ability to handle missing content and insufficient object detail.

Object Recognition Semantic Similarity +1

Enabling My Robot To Play Pictionary : Recurrent Neural Networks For Sketch Recognition

1 code implementation11 Aug 2016 Ravi Kiran Sarvadevabhatla, Jogendra Kundu, Babu R. Venkatesh

In our work, we propose a recurrent neural network architecture for sketch object recognition which exploits the long-term sequential and structural regularities in stroke data in a scalable manner.

Object Recognition Sketch Recognition

SwiDeN : Convolutional Neural Networks For Depiction Invariant Object Recognition

1 code implementation29 Jul 2016 Ravi Kiran Sarvadevabhatla, Shiv Surya, Srinivas S. S. Kruthiventi, Venkatesh Babu R

Current state of the art object recognition architectures achieve impressive performance but are typically specialized for a single depictive style (e. g. photos only, sketches only).

Depiction Invariant Object Recognition

A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

no code implementations25 Jan 2016 Suraj Srinivas, Ravi Kiran Sarvadevabhatla, Konda Reddy Mopuri, Nikita Prabhu, Srinivas S. S. Kruthiventi, R. Venkatesh Babu

With this new paradigm, every problem in computer vision is now being re-examined from a deep learning perspective.

Analyzing structural characteristics of object category representations from their semantic-part distributions

no code implementations15 Sep 2015 Ravi Kiran Sarvadevabhatla, Venkatesh Babu R

Studies from neuroscience show that part-mapping computations are employed by human visual system in the process of object recognition.

Object Recognition

Expresso : A user-friendly GUI for Designing, Training and Exploring Convolutional Neural Networks

1 code implementation25 May 2015 Ravi Kiran Sarvadevabhatla, R. Venkatesh Babu

With a view to provide a user-friendly interface for designing, training and developing deep learning frameworks, we have developed Expresso, a GUI tool written in Python.

Freehand Sketch Recognition Using Deep Features

no code implementations1 Feb 2015 Ravi Kiran Sarvadevabhatla, R. Venkatesh Babu

Therefore, analyzing such sparse sketches can aid our understanding of the neuro-cognitive processes involved in visual representation and recognition.

Sketch-Based Image Retrieval Sketch Recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.