14 citations · 48 across the 18 of their papers we have counts for
22 papers
Non-linear Motion Estimation for Video Frame Interpolation using Space-time Convolutions
Saikat Dutta, Arulkumar Subramaniam, Anurag Mittal
Video frame interpolation aims to synthesize one or multiple frames between two consecutive frames in a video. It has a wide range of applications including slow-motion video gener…
Co-segmentation Inspired Attention Module for Video-based Computer Vision Tasks
Arulkumar Subramaniam, Jayesh Vaidya, Muhammed Abdul Majeed Ameen +2
Video-based computer vision tasks can benefit from estimation of the salient regions and interactions between those regions. Traditionally, this has been done by identifying the ob…
On the Significance of Question Encoder Sequence Model in the Out-of-Distribution Performance in Visual Question Answering
Gouthaman KV, Anurag Mittal
Generalizing beyond the experiences has a significant role in developing practical AI systems. It has been shown that current Visual Question Answering (VQA) models are over-depend…
Face Age Progression With Attribute Manipulation
Sinzith Tatikonda, Athira Nambiar, Anurag Mittal
Face is one of the predominant means of person recognition. In the process of ageing, human face is prone to many factors such as time, attributes, weather and other subject specif…
Efficient Space-time Video Super Resolution using Low-Resolution Flow and Mask Upsampling
Saikat Dutta, Nisarg A. Shah, Anurag Mittal
This paper explores an efficient solution for Space-time Super-Resolution, aiming to generate High-resolution Slow-motion videos from Low Resolution and Low Frame rate videos. A si…
Domain Adaptive Knowledge Distillation for Driving Scene Semantic Segmentation
Divya Kothandaraman, Athira Nambiar, Anurag Mittal
Practical autonomous driving systems face two crucial challenges: memory constraints and domain gap issues. In this paper, we present a novel approach to learn domain adaptive know…
MARNet: Multi-Abstraction Refinement Network for 3D Point Cloud Analysis
Rahul Chakwate, Arulkumar Subramaniam, Anurag Mittal
Representation learning from 3D point clouds is challenging due to their inherent nature of permutation invariance and irregular distribution in space. Existing deep learning metho…
WDN: A Wide and Deep Network to Divide-and-Conquer Image Super-resolution
Vikram Singh, Anurag Mittal
Divide and conquer is an established algorithm design paradigm that has proven itself to solve a variety of problems efficiently. However, it is yet to be fully explored in solving…
Linguistically-aware Attention for Reducing the Semantic-Gap in Vision-Language Tasks
Gouthaman KV, Athira Nambiar, Kancheti Sai Srinivas +1
Attention models are widely used in Vision-language (V-L) tasks to perform the visual-textual correlation. Humans perform such a correlation with a strong linguistic understanding…
Reducing Language Biases in Visual Question Answering with Visually-Grounded Question Encoder
Gouthaman KV, Anurag Mittal
Recent studies have shown that current VQA models are heavily biased on the language priors in the train set to answer the question, irrespective of the image. E.g., overwhelmingly…
Stacked Adversarial Network for Zero-Shot Sketch based Image Retrieval
Anubha Pandey, Ashish Mishra, Vinay Kumar Verma +2
Conventional approaches to Sketch-Based Image Retrieval (SBIR) assume that the data of all the classes are available during training. The assumption may not always be practical sin…
Blind Deblurring Using GANs
Manoj Kumar Lenka, Anubha Pandey, Anurag Mittal
Deblurring is the task of restoring a blurred image to a sharp one, retrieving the information lost due to the blur. In blind deblurring we have no information regarding the blur k…
A Zero-Shot Framework for Sketch-based Image Retrieval
Sasi Kiran Yelamarthi, Shiva Krishna Reddy, Ashish Mishra +1
Sketch-based image retrieval (SBIR) is the task of retrieving images from a natural image database that correspond to a given hand-drawn sketch. Ideally, an SBIR model should learn…
A Generative Approach to Zero-Shot and Few-Shot Action Recognition
Ashish Mishra, Vinay Kumar Verma, M Shiva Krishna Reddy +3
We present a generative framework for zero-shot action recognition where some of the possible action classes do not occur in the training data. Our approach is based on modeling ea…
A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders
Ashish Mishra, M Shiva Krishna Reddy, Anurag Mittal +1
Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language…
CoMaL Tracking: Tracking Points at the Object Boundaries
Santhosh K. Ramakrishnan, Swarna Kamlam Ravindran, Anurag Mittal
Traditional point tracking algorithms such as the KLT use local 2D information aggregation for feature detection and tracking, due to which their performance degrades at the object…
An Empirical Evaluation of Visual Question Answering for Novel Objects
Santhosh K. Ramakrishnan, Ambar Pal, Gaurav Sharma +1
We study the problem of answering questions about images in the harder setting, where the test questions and corresponding images contain novel objects, which were not queried abou…
Bi-modal First Impressions Recognition using Temporally Ordered Deep Audio and Stochastic Visual Features
Arulkumar Subramaniam, Vismay Patel, Ashish Mishra +2
We propose a novel approach for First Impressions Recognition in terms of the Big Five personality-traits from short videos. The Big Five personality traits is a model to describe…
Sketch-based Image Retrieval from Millions of Images under Rotation, Translation and Scale Variations
Sarthak Parui, Anurag Mittal
Proliferation of touch-based devices has made sketch-based image retrieval practical. While many methods exist for sketch-based object detection/image retrieval on small datasets,…
Adaptive Locally Affine-Invariant Shape Matching
Smit Marvaniya, Raj Gupta, Anurag Mittal
Matching deformable objects using their shapes is an important problem in computer vision since shape is perhaps the most distinguishable characteristic of an object. The problem i…
Mixture of Parts Revisited: Expressive Part Interactions for Pose Estimation
Anoop Katti, Anurag Mittal
Part-based models with restrictive tree-structured interactions for the Human Pose Estimation problem, leaves many part interactions unhandled. Two of the most common and strong ma…
CoMIC: Good features for detection and matching at object boundaries
Swarna Kamlam Ravindran, Anurag Mittal
Feature or interest points typically use information aggregation in 2D patches which does not remain stable at object boundaries when there is object motion against a significantly…