Search Results for author: Abhishek Sharma

Found 36 papers, 16 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.

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

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

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, 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 +2

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 Region Proposal

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.

Eye Tracking Gaze Estimation +3

Towards Automatic Generation of Questions from Long Answers

no code implementations10 Apr 2020 Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma, Abhyuday Jagannatha, David Jacobs, Hal Daumé III

Therefore, we propose a novel evaluation benchmark to assess the performance of existing AQG systems for long-text answers.

Information Retrieval Question Generation

Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence

2 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 implementations15 Oct 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.

Multi-Person 3D Human Pose Estimation from Monocular Images

no code implementations24 Sep 2019 Rishabh Dabral, Nitesh B. Gundavarapu, Rahul Mitra, Abhishek Sharma, Ganesh Ramakrishnan, Arjun Jain

Multi-person 3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data.

3D Human Pose Estimation

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.

Classification General Classification +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 +1

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.

Graphics

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.

Object Discovery Semantic Segmentation

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.

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

Learning 3D Human Pose from Structure and Motion

1 code implementation ECCV 2018 Rishabh Dabral, Anurag Mundhada, Uday Kusupati, Safeer Afaque, Abhishek Sharma, Arjun Jain

3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data.

Monocular 3D Human Pose Estimation

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.

Denoising

Controlling Search in Very large Commonsense Knowledge Bases: A Machine Learning Approach

no code implementations14 Mar 2016 Abhishek Sharma, Michael Witbrock, Keith Goolsbey

Results show that these methods lead to an order of magnitude reduction in inference time.

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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