Search Results for author: Chetan Arora

Found 52 papers, 21 papers with code

Is Sharing of Egocentric Video Giving Away Your Biometric Signature?

no code implementations ECCV 2020 Daksh Thapar, Chetan Arora, Aditya Nigam

In this work, we create a novel kind of privacy attack by extracting the wearer’s gait profile, a well known biometric signature, from such optical flow in the egocentric videos.

Optical Flow Estimation

Model Generation from Requirements with LLMs: an Exploratory Study

no code implementations9 Apr 2024 Alessio Ferrari, Sallam Abualhaija, Chetan Arora

Complementing natural language (NL) requirements with graphical models can improve stakeholders' communication and provide directions for system design.

ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth Estimation

1 code implementation CVPR 2024 Suraj Patni, Aradhye Agarwal, Chetan Arora

We argue that the embedding vector from a ViT model, pre-trained on a large dataset, captures greater relevant information for SIDE than the usual route of generating pseudo image captions, followed by CLIP based text embeddings.

Depth Prediction Monocular Depth Estimation

FocusMAE: Gallbladder Cancer Detection from Ultrasound Videos with Focused Masked Autoencoders

1 code implementation CVPR 2024 Soumen Basu, Mayuna Gupta, Chetan Madan, Pankaj Gupta, Chetan Arora

We validate the proposed methods on the curated dataset, and report a new state-of-the-art (SOTA) accuracy of 96. 4% for the GBC detection problem, against an accuracy of 84% by current Image-based SOTA - GBCNet, and RadFormer, and 94. 7% by Video-based SOTA - AdaMAE.

Gallbladder Cancer Detection Representation Learning

Fairness Concerns in App Reviews: A Study on AI-based Mobile Apps

no code implementations16 Jan 2024 Ali Rezaei Nasab, Maedeh Dashti, Mojtaba Shahin, Mansooreh Zahedi, Hourieh Khalajzadeh, Chetan Arora, Peng Liang

Leveraging the ground-truth dataset, we developed and evaluated a set of machine learning and deep learning models that distinguish fairness reviews from non-fairness reviews.

Fairness

United We Stand, Divided We Fall: UnityGraph for Unsupervised Procedure Learning from Videos

no code implementations6 Nov 2023 Siddhant Bansal, Chetan Arora, C. V. Jawahar

Given multiple videos of the same task, procedure learning addresses identifying the key-steps and determining their order to perform the task.

Procedure Learning

Model-driven Engineering for Machine Learning Components: A Systematic Literature Review

no code implementations1 Nov 2023 Hira Naveed, Chetan Arora, Hourieh Khalajzadeh, John Grundy, Omar Haggag

Through this SLR, we wanted to analyze existing studies, including their motivations, MDE solutions, evaluation techniques, key benefits and limitations.

Anomaly Detection Decision Making

Gall Bladder Cancer Detection from US Images with Only Image Level Labels

no code implementations11 Sep 2023 Soumen Basu, Ashish Papanai, Mayank Gupta, Pankaj Gupta, Chetan Arora

We posit that even when we have only the image level label, still formulating the problem as object detection (with bounding box output) helps a deep neural network (DNN) model focus on the relevant region of interest.

Image Classification Object +2

UTRNet: High-Resolution Urdu Text Recognition In Printed Documents

1 code implementation27 Jun 2023 Abdur Rahman, Arjun Ghosh, Chetan Arora

To address the limitations of previous works, which struggle to generalize to the intricacies of the Urdu script and the lack of sufficient annotated real-world data, we have introduced the UTRSet-Real, a large-scale annotated real-world dataset comprising over 11, 000 lines and UTRSet-Synth, a synthetic dataset with 20, 000 lines closely resembling real-world and made corrections to the ground truth of the existing IIITH dataset, making it a more reliable resource for future research.

Line Detection Optical Character Recognition (OCR) +2

Stop Words for Processing Software Engineering Documents: Do they Matter?

no code implementations18 Mar 2023 Yaohou Fan, Chetan Arora, Christoph Treude

In this work, we investigate the usefulness of stop word removal in a software engineering context.

General Knowledge

Requirements Engineering Framework for Human-centered Artificial Intelligence Software Systems

no code implementations6 Mar 2023 Khlood Ahmad, Mohamed Abdelrazek, Chetan Arora, Arbind Agrahari Baniya, Muneera Bano, John Grundy

[Method] In this paper, we present a new framework developed based on human-centered AI guidelines and a user survey to aid in collecting requirements for human-centered AI-based software.

Attention Attention Everywhere: Monocular Depth Prediction with Skip Attention

1 code implementation17 Oct 2022 Ashutosh Agarwal, Chetan Arora

Typically, a skip connection module is used to fuse the encoder and decoder features, which comprises of feature map concatenation followed by a convolution operation.

Ranked #19 on Monocular Depth Estimation on KITTI Eigen split (using extra training data)

Decoder Depth Prediction +1

Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift

1 code implementation13 Oct 2022 Sharat Agarwal, Saket Anand, Chetan Arora

In this work, we propose an ADA strategy, which given a frame, identifies a set of classes that are hardest for the model to predict accurately, thereby recommending semantically meaningful regions to be annotated in a selected frame.

Active Learning Domain Adaptation +1

Unsupervised Contrastive Learning of Image Representations from Ultrasound Videos with Hard Negative Mining

1 code implementation26 Jul 2022 Soumen Basu, Somanshu Singla, Mayank Gupta, Pratyaksha Rana, Pankaj Gupta, Chetan Arora

We further validate the generalizability of our method on a publicly available lung US image dataset of COVID-19 pathologies and show an improvement of 1. 5% compared to SOTA.

Contrastive Learning

My View is the Best View: Procedure Learning from Egocentric Videos

1 code implementation22 Jul 2022 Siddhant Bansal, Chetan Arora, C. V. Jawahar

Instead, we propose to use the signal provided by the temporal correspondences between key-steps across videos.

Procedure Learning

Depthformer : Multiscale Vision Transformer For Monocular Depth Estimation With Local Global Information Fusion

1 code implementation10 Jul 2022 Ashutosh Agarwal, Chetan Arora

We also propose a Transbins module that divides the depth range into bins whose center value is estimated adaptively per image.

Ranked #29 on Monocular Depth Estimation on KITTI Eigen split (using extra training data)

Decoder Depth Prediction +2

TAPHSIR: Towards AnaPHoric Ambiguity Detection and ReSolution In Requirements

no code implementations21 Jun 2022 Saad Ezzini, Sallam Abualhaija, Chetan Arora, Mehrdad Sabetzadeh

We introduce TAPHSIR, a tool for anaphoric ambiguity detection and anaphora resolution in requirements.

Language Modelling

A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration

1 code implementation CVPR 2022 Ramya Hebbalaguppe, Jatin Prakash, Neelabh Madan, Chetan Arora

We show that training with MDCA leads to better-calibrated models in terms of Expected Calibration Error ( ECE ), and Static Calibration Error ( SCE ) on image classification, and segmentation tasks.

Image Classification Semantic Segmentation

Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey

no code implementations22 Feb 2022 Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak, Kevin Lee, Chetan Arora, Ali Hassani, Arkady Zaslavsky

Indeed, Adversarial Artificial Intelligence (AI) which refers to a set of techniques that attempt to fool machine learning models with deceptive data, is a growing threat in the AI and machine learning research community, in particular for machine-critical applications.

Adversarial Attack BIG-bench Machine Learning +3

Merry Go Round: Rotate a Frame and Fool a DNN

no code implementations CVPR 2022 Daksh Thapar, Aditya Nigam, Chetan Arora

On the other hand DNNs are known to be susceptible to Adversarial Attacks (AAs) which add im-perceptible noise to the input.

Action Detection Activity Detection +1

Attention Guided Cosine Margin For Overcoming Class-Imbalance in Few-Shot Road Object Detection

no code implementations12 Nov 2021 Ashutosh Agarwal, Anay Majee, Anbumani Subramanian, Chetan Arora

To overcome these pitfalls in metric learning based FSOD techniques, we introduce Attention Guided Cosine Margin (AGCM) that facilitates the creation of tighter and well separated class-specific feature clusters in the classification head of the object detector.

Few-Shot Object Detection Meta-Learning +2

Multi-Domain Incremental Learning for Semantic Segmentation

1 code implementation23 Oct 2021 Prachi Garg, Rohit Saluja, Vineeth N Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar

Recent efforts in multi-domain learning for semantic segmentation attempt to learn multiple geographical datasets in a universal, joint model.

Incremental Learning Scene Segmentation +1

Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias

1 code implementation20 Oct 2021 Sharat Agarwal, Sumanyu Muku, Saket Anand, Chetan Arora

Through a series of experiments, we validate that curating contextually fair data helps make model predictions fair by balancing the true positive rate for the protected class across groups without compromising on the model's overall performance.

Active Learning Attribute +3

Anonymizing Egocentric Videos

no code implementations ICCV 2021 Daksh Thapar, Aditya Nigam, Chetan Arora

In a more damaging scenario, one can even recognize a wearer using hand gestures from egocentric videos, or identify a wearer in third person videos such as from a surveillance camera.

Activity Recognition object-detection +2

Contextual Diversity for Active Learning

1 code implementation ECCV 2020 Sharat Agarwal, Himanshu Arora, Saket Anand, Chetan Arora

Contextual Diversity (CD) hinges on a crucial observation that the probability vector predicted by a CNN for a region of interest typically contains information from a larger receptive field.

Active Learning Image Classification +3

CovidAID: COVID-19 Detection Using Chest X-Ray

5 code implementations21 Apr 2020 Arpan Mangal, Surya Kalia, Harish Rajgopal, Krithika Rangarajan, Vinay Namboodiri, Subhashis Banerjee, Chetan Arora

This may be useful in an inpatient setting where the present systems are struggling to decide whether to keep the patient in the ward along with other patients or isolate them in COVID-19 areas.

Diversity in Fashion Recommendation using Semantic Parsing

1 code implementation18 Oct 2019 Sagar Verma, Sukhad Anand, Chetan Arora, Atul Rai

In this paper, we propose to recommend images by explicitly learning and exploiting part based similarity.

Retrieval Semantic Parsing

Making Third Person Techniques Recognize First-Person Actions in Egocentric Videos

1 code implementation17 Oct 2019 Sagar Verma, Pravin Nagar, Divam Gupta, Chetan Arora

Unlike third person domain, researchers have divided first-person actions into two categories: involving hand-object interactions and the ones without, and developed separate techniques for the two action categories.

Action Recognition

U-SegNet: Fully Convolutional Neural Network based Automated Brain tissue segmentation Tool

no code implementations12 Jun 2018 Pulkit Kumar, Pravin Nagar, Chetan Arora, Anubha Gupta

Automated brain tissue segmentation into white matter (WM), gray matter (GM), and cerebro-spinal fluid (CSF) from magnetic resonance images (MRI) is helpful in the diagnosis of neuro-disorders such as epilepsy, Alzheimer's, multiple sclerosis, etc.

Segmentation

A Joint 3D-2D based Method for Free Space Detection on Roads

no code implementations6 Nov 2017 Suvam Patra, Pranjal Maheshwari, Shashank Yadav, Chetan Arora, Subhashis Banerjee

Finally, we use the obtained road segmentation with the 3D depth data from monocular SLAM to detect the free space for the navigation purposes.

Autonomous Driving General Classification +4

Robust Monocular SLAM for Egocentric Videos

no code implementations18 Jul 2017 Suvam Patra, Kartikeya Gupta, Faran Ahmad, Chetan Arora, Subhashis Banerjee

The incremental nature of SOTA SLAM, in the presence of unreliable pose and 3D estimates in egocentric videos, with no opportunities for global loop closures, generates drifts and leads to the eventual failures of such techniques.

Simultaneous Localization and Mapping

Min Norm Point Algorithm for Higher Order MRF-MAP Inference

no code implementations CVPR 2016 Ishant Shanu, Chetan Arora, Parag Singla

Current state of the art inference algorithms for general submodular function takes many hours for problems with clique size 16, and fail to scale beyond.

EgoSampling: Wide View Hyperlapse from Egocentric Videos

no code implementations26 Apr 2016 Tavi Halperin, Yair Poleg, Chetan Arora, Shmuel Peleg

However, this accentuates the shake caused by natural head motion in an egocentric video, making the fast forwarded video useless.

Trajectory Aligned Features For First Person Action Recognition

no code implementations7 Apr 2016 Suriya Singh, Chetan Arora, C. V. Jawahar

Objects present in the scene and hand gestures of the wearer are the most important cues for first person action recognition but are difficult to segment and recognize in an egocentric video.

Action Recognition Point Tracking +1

Compact CNN for Indexing Egocentric Videos

no code implementations28 Apr 2015 Yair Poleg, Ariel Ephrat, Shmuel Peleg, Chetan Arora

Furthermore, our CNN is able to recognize whether a video is egocentric or not with 99. 2% accuracy, up by 24% from current state-of-the-art.

Activity Recognition Optical Flow Estimation

EgoSampling: Fast-Forward and Stereo for Egocentric Videos

no code implementations CVPR 2015 Yair Poleg, Tavi Halperin, Chetan Arora, Shmuel Peleg

While egocentric cameras like GoPro are gaining popularity, the videos they capture are long, boring, and difficult to watch from start to end.

Fast Approximate Inference in Higher Order MRF-MAP Labeling Problems

no code implementations CVPR 2014 Chetan Arora, Subhashis Banerjee, Prem Kalra, S. N. Maheshwari

Generic Cuts (GC) of Arora et al. [9] shows that when potentials are submodular, inference problems can be solved optimally in polynomial time for fixed size cliques.

Multi Label Generic Cuts: Optimal Inference in Multi Label Multi Clique MRF-MAP Problems

no code implementations CVPR 2014 Chetan Arora, S. N. Maheshwari

We exploit sparseness in the feasible configurations of the transformed 2-label problem to suggest an improvement to Generic Cuts [3] to solve the 2-label problems efficiently.

Temporal Segmentation of Egocentric Videos

no code implementations CVPR 2014 Yair Poleg, Chetan Arora, Shmuel Peleg

Two sources of information for video segmentation are (i) the motion of the camera wearer, and (ii) the objects and activities recorded in the video.

Segmentation Video Segmentation +1

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