Search Results for author: Abhishek Sharma

Found 50 papers, 17 papers with code

Neural Conversational QA: Learning to Reason vs Exploiting Patterns

no code implementations EMNLP 2020 Nikhil Verma, Abhishek Sharma, Dhiraj Madan, Danish Contractor, Harshit Kumar, Sachindra Joshi

Neural Conversational QA tasks such as ShARC require systems to answer questions based on the contents of a given passage.

Interactive Post-Editing for Verbosity Controlled Translation

no code implementations COLING 2022 Prabhakar Gupta, Anil Nelakanti, Grant M. Berry, Abhishek Sharma

We explore Interactive Post-Editing (IPE) models for human-in-loop translation to help correct translation errors and rephrase it with a desired style variation.

Machine Translation Translation

Adapting Neural Machine Translation for Automatic Post-Editing

no code implementations WMT (EMNLP) 2021 Abhishek Sharma, Prabhakar Gupta, Anil Nelakanti

Automatic post-editing (APE) models are usedto correct machine translation (MT) system outputs by learning from human post-editing patterns.

Automatic Post-Editing Translation

Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation

no code implementations10 Sep 2022 Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje

Federated Learning (FL) is a machine learning paradigm where local nodes collaboratively train a central model while the training data remains decentralized.

Federated Learning Image Classification +4

Surya Namaskar: real-time advanced yoga pose recognition and correction for smart healthcare

no code implementations6 Sep 2022 Abhishek Sharma, Pranjal Sharma, Darshan Pincha, Prateek Jain

Nowadays, yoga has gained worldwide attention because of increasing levels of stress in the modern way of life, and there are many ways or resources to learn yoga.

Real-time Recognition of Yoga Poses using computer Vision for Smart Health Care

no code implementations19 Jan 2022 Abhishek Sharma, Yash Shah, Yash Agrawal, Prateek Jain

In this work, a self-assistance based yoga posture identification technique is developed, which helps users to perform Yoga with the correction feature in Real-time.

Joint Symmetry Detection and Shape Matching for Non-Rigid Point Cloud

no code implementations5 Dec 2021 Abhishek Sharma, Maks Ovsjanikov

Despite the success of deep functional maps in non-rigid 3D shape matching, there exists no learning framework that models both self-symmetry and shape matching simultaneously.

Symmetry Detection

Object-Aware Cropping for Self-Supervised Learning

1 code implementation1 Dec 2021 Shlok Mishra, Anshul Shah, Ankan Bansal, Abhyuday Jagannatha, Abhishek Sharma, David Jacobs, Dilip Krishnan

This assumption is mostly satisfied in datasets such as ImageNet where there is a large, centered object, which is highly likely to be present in random crops of the full image.

Data Augmentation object-detection +2

On Learning Prediction-Focused Mixtures

no code implementations25 Oct 2021 Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Finale Doshi-Velez

Probabilistic models help us encode latent structures that both model the data and are ideally also useful for specific downstream tasks.

Time Series Analysis

Learning Canonical Embedding for Non-rigid Shape Matching

no code implementations6 Oct 2021 Abhishek Sharma, Maks Ovsjanikov

This paper provides a novel framework that learns canonical embeddings for non-rigid shape matching.

Scale Normalized Image Pyramids with AutoFocus for Object Detection

1 code implementation10 Feb 2021 Bharat Singh, Mahyar Najibi, Abhishek Sharma, Larry S. Davis

The resulting algorithm is referred to as AutoFocus and results in a 2. 5-5 times speed-up during inference when used with SNIP.

object-detection Object Detection

Matrix Decomposition on Graphs: A Functional View

no code implementations5 Feb 2021 Abhishek Sharma, Maks Ovsjanikov

We propose a functional view of matrix decomposition problems on graphs such as geometric matrix completion and graph regularized dimensionality reduction.

Dimensionality Reduction Matrix Completion

Ensemble Attention Distillation for Privacy-Preserving Federated Learning

no code implementations ICCV 2021 Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje

Such decentralized training naturally leads to issues of imbalanced or differing data distributions among the local models and challenges in fusing them into a central model.

Federated Learning Privacy Preserving

Weakly Supervised Deep Functional Maps for Shape Matching

1 code implementation NeurIPS 2020 Abhishek Sharma, Maks Ovsjanikov

We show empirically the minimum components for obtaining state-of-the-art results with different loss functions, supervised as well as unsupervised.

Learning Visual Representations for Transfer Learning by Suppressing Texture

1 code implementation3 Nov 2020 Shlok Mishra, Anshul Shah, Ankan Bansal, Janit Anjaria, Jonghyun Choi, Abhinav Shrivastava, Abhishek Sharma, David Jacobs

Recent literature has shown that features obtained from supervised training of CNNs may over-emphasize texture rather than encoding high-level information.

Image Classification object-detection +3

Geometric Matrix Completion: A Functional View

1 code implementation29 Sep 2020 Abhishek Sharma, Maks Ovsjanikov

We propose a totally functional view of geometric matrix completion problem.

Matrix Completion

Weakly Supervised Deep Functional Map for Shape Matching

2 code implementations28 Sep 2020 Abhishek Sharma, Maks Ovsjanikov

We show empirically minimum components for obtaining state of the art results with different loss functions, supervised as well as unsupervised.

ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors

1 code implementation19 Jul 2020 Rohun Tripathi, Vasu Singla, Mahyar Najibi, Bharat Singh, Abhishek Sharma, Larry Davis

The widely adopted sequential variant of Non Maximum Suppression (or Greedy-NMS) is a crucial module for object-detection pipelines.

object-detection Object Detection +1

Price Optimization in Fashion E-commerce

no code implementations10 Jul 2020 Sajan Kedia, Samyak Jain, Abhishek Sharma

Thus we obtain multiple price demand pairs for each product and we have to choose one of them for the live platform.

OpenEDS2020: Open Eyes Dataset

no code implementations8 May 2020 Cristina Palmero, Abhishek Sharma, Karsten Behrendt, Kapil Krishnakumar, Oleg V. Komogortsev, Sachin S. Talathi

We present the second edition of OpenEDS dataset, OpenEDS2020, a novel dataset of eye-image sequences captured at a frame rate of 100 Hz under controlled illumination, using a virtual-reality head-mounted display mounted with two synchronized eye-facing cameras.

Gaze Estimation Gaze Prediction +1

Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence

3 code implementations CVPR 2020 Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov

We present a novel learning-based approach for computing correspondences between non-rigid 3D shapes.

Listwise Learning to Rank with Deep Q-Networks

no code implementations13 Feb 2020 Abhishek Sharma

Learning to Rank is the problem involved with ranking a sequence of documents based on their relevance to a given query.

Decision Making Learning-To-Rank +1

Reinforcement learning with a network of spiking agents

2 code implementations NeurIPS Workshop Neuro_AI 2019 Sneha Aenugu, Abhishek Sharma, Sasikiran Yelamarthi, Hananel Hazan, Philip S. Thomas, Robert Kozma

Neuroscientific theory suggests that dopaminergic neurons broadcast global reward prediction errors to large areas of the brain influencing the synaptic plasticity of the neurons in those regions.

reinforcement-learning Reinforcement Learning (RL)

Neural Conversational QA: Learning to Reason v.s. Exploiting Patterns

2 code implementations9 Sep 2019 Nikhil Verma, Abhishek Sharma, Dhiraj Madan, Danish Contractor, Harshit Kumar, Sachindra Joshi

On studying recent state-of-the-art models on the ShARCQA task, we found indications that the models learn spurious clues/patterns in the dataset.

On the Robustness of Human Pose Estimation

no code implementations18 Aug 2019 Sahil Shah, Naman jain, Abhishek Sharma, Arjun Jain

This paper provides a comprehensive and exhaustive study of adversarial attacks on human pose estimation models and the evaluation of their robustness.

General Classification Pose Estimation +2

Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation

no code implementations CVPR 2020 Rahul Mitra, Nitesh B. Gundavarapu, Abhishek Sharma, Arjun Jain

The best performing methods for 3D human pose estimation from monocular images require large amounts of in-the-wild 2D and controlled 3D pose annotated datasets which are costly and require sophisticated systems to acquire.

3D Human Pose Estimation Metric Learning +2

Exploration of Self-Propelling Droplets Using a Curiosity Driven Robotic Assistant

no code implementations22 Apr 2019 Jonathan Grizou, Laurie J. Points, Abhishek Sharma, Leroy Cronin

We describe a chemical robotic assistant equipped with a curiosity algorithm (CA) that can efficiently explore the state a complex chemical system can exhibit.

ZoomOut: Spectral Upsampling for Efficient Shape Correspondence

2 code implementations16 Apr 2019 Simone Melzi, Jing Ren, Emanuele Rodolà, Abhishek Sharma, Peter Wonka, Maks Ovsjanikov

Our main observation is that high quality maps can be obtained even if the input correspondences are noisy or are encoded by a small number of coefficients in a spectral basis.


Unsupervised Deep Learning for Structured Shape Matching

4 code implementations ICCV 2019 Jean-Michel Roufosse, Abhishek Sharma, Maks Ovsjanikov

We present a novel method for computing correspondences across 3D shapes using unsupervised learning.

Foreground Clustering for Joint Segmentation and Localization in Videos and Images

no code implementations NeurIPS 2018 Abhishek Sharma

This paper presents a novel framework in which video/image segmentation and localization are cast into a single optimization problem that integrates information from low level appearance cues with that of high level localization cues in a very weakly supervised manner.

Image Segmentation Object Discovery +2

DYAN: A Dynamical Atoms-Based Network for Video Prediction

no code implementations ECCV 2018 Wenqian Liu, Abhishek Sharma, Octavia Camps, Mario Sznaier

The ability to anticipate the future is essential when making real time critical decisions, provides valuable information to understand dynamic natural scenes, and can help unsupervised video representation learning.

Representation Learning Video Prediction

Rate of Change Analysis for Interestingness Measures

no code implementations14 Dec 2017 Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran

We present a comprehensive analysis of 50 interestingness measures and classify them in accordance with the two properties.

Association General Classification

R-FCN-3000 at 30fps: Decoupling Detection and Classification

2 code implementations CVPR 2018 Bharat Singh, Hengduo Li, Abhishek Sharma, Larry S. Davis

Our approach is a modification of the R-FCN architecture in which position-sensitive filters are shared across different object classes for performing localization.

Classification General Classification

One Shot Joint Colocalization and Cosegmentation

no code implementations17 May 2017 Abhishek Sharma

This paper presents a novel framework in which image cosegmentation and colocalization are cast into a single optimization problem that integrates information from low level appearance cues with that of high level localization cues in a very weakly supervised manner.

Multi-Task Learning

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

1 code implementation13 Apr 2016 Abhishek Sharma, Oliver Grau, Mario Fritz

Prior work has shown encouraging results on problems ranging from shape completion to recognition.


Deep Hierarchical Parsing for Semantic Segmentation

no code implementations CVPR 2015 Abhishek Sharma, Oncel Tuzel, David W. Jacobs

We propose to tackle this problem by including the classification loss of the internal nodes of the random parse trees in the original RCPN loss function.

General Classification Scene Parsing +1

Locally Scale-Invariant Convolutional Neural Networks

no code implementations16 Dec 2014 Angjoo Kanazawa, Abhishek Sharma, David Jacobs

We show on a modified MNIST dataset that when faced with scale variation, building in scale-invariance allows ConvNets to learn more discriminative features with reduced chances of over-fitting.

Recursive Context Propagation Network for Semantic Scene Labeling

no code implementations NeurIPS 2014 Abhishek Sharma, Oncel Tuzel, Ming-Yu Liu

Then a top-down propagation of the aggregated information takes place that enhances the contextual information of each local feature.

Scene Labeling

A Sentence Is Worth a Thousand Pixels

no code implementations CVPR 2013 Sanja Fidler, Abhishek Sharma, Raquel Urtasun

We are interested in holistic scene understanding where images are accompanied with text in the form of complex sentential descriptions.

Re-Ranking Scene Understanding +2

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