111 citations · 163 across the 14 of their papers we have counts for
18 papers
Object-Aware Cropping for Self-Supervised Learning
Shlok Mishra, Anshul Shah, Ankan Bansal +5
A core component of the recent success of self-supervised learning is cropping data augmentation, which selects sub-regions of an image to be used as positive views in the self-sup…
Learning Canonical Embedding for Non-rigid Shape Matching
Abhishek Sharma, Maks Ovsjanikov
This paper provides a novel framework that learns canonical embeddings for non-rigid shape matching. In contrast to prior work in this direction, our framework is trained end-to-en…
Scale Normalized Image Pyramids with AutoFocus for Object Detection
Bharat Singh, Mahyar Najibi, Abhishek Sharma +1
We present an efficient foveal framework to perform object detection. A scale normalized image pyramid (SNIP) is generated that, like human vision, only attends to objects within a…
Learning Visual Representations for Transfer Learning by Suppressing Texture
Shlok Mishra, Anshul Shah, Ankan Bansal +5
Recent literature has shown that features obtained from supervised training of CNNs may over-emphasize texture rather than encoding high-level information. In self-supervised learn…
Geometric Matrix Completion: A Functional View
Abhishek Sharma, Maks Ovsjanikov
We propose a totally functional view of geometric matrix completion problem. Differently from existing work, we propose a novel regularization inspired from the functional map lite…
ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors
Rohun Tripathi, Vasu Singla, Mahyar Najibi +3
The widely adopted sequential variant of Non Maximum Suppression (or Greedy-NMS) is a crucial module for object-detection pipelines. Unfortunately, for the region proposal stage of…
OpenEDS2020: Open Eyes Dataset
Cristina Palmero, Abhishek Sharma, Karsten Behrendt +3
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 virt…
Towards Automatic Generation of Questions from Long Answers
Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma +3
Automatic question generation (AQG) has broad applicability in domains such as tutoring systems, conversational agents, healthcare literacy, and information retrieval. Existing eff…
Listwise Learning to Rank with Deep Q-Networks
Abhishek Sharma
Learning to Rank is the problem involved with ranking a sequence of documents based on their relevance to a given query. Deep Q-Learning has been shown to be a useful method for tr…
Reinforcement learning with a network of spiking agents
Sneha Aenugu, Abhishek Sharma, Sasikiran Yelamarthi +3
Neuroscientific theory suggests that dopaminergic neurons broadcast global reward prediction errors to large areas of the brain influencing the synaptic plasticity of the neurons i…
Multi-Person 3D Human Pose Estimation from Monocular Images
Rishabh Dabral, Nitesh B Gundavarapu, Rahul Mitra +3
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. We propose HG-RCNN, a…
On the Robustness of Human Pose Estimation
Sahil Shah, Naman Jain, Abhishek Sharma +1
This paper provides a comprehensive and exhaustive study of adversarial attacks on human pose estimation models and the evaluation of their robustness. Besides highlighting the imp…
Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation
Rahul Mitra, Nitesh B. Gundavarapu, Abhishek Sharma +1
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 an…
Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking
Saurabh Sharma, Pavan Teja Varigonda, Prashast Bindal +2
Monocular 3D human-pose estimation from static images is a challenging problem, due to the curse of dimensionality and the ill-posed nature of lifting 2D-to-3D. In this paper, we p…
DYAN: A Dynamical Atoms-Based Network for Video Prediction
Wenqian Liu, Abhishek Sharma, Octavia Camps +1
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 unsuper…
R-FCN-3000 at 30fps: Decoupling Detection and Classification
Bharat Singh, Hengduo Li, Abhishek Sharma +1
We present R-FCN-3000, a large-scale real-time object detector in which objectness detection and classification are decoupled. To obtain the detection score for an RoI, we multiply…
Deep Hierarchical Parsing for Semantic Segmentation
Abhishek Sharma, Oncel Tuzel, David W. Jacobs
This paper proposes a learning-based approach to scene parsing inspired by the deep Recursive Context Propagation Network (RCPN). RCPN is a deep feed-forward neural network that ut…
Locally Scale-Invariant Convolutional Neural Networks
Angjoo Kanazawa, Abhishek Sharma, David Jacobs
Convolutional Neural Networks (ConvNets) have shown excellent results on many visual classification tasks. With the exception of ImageNet, these datasets are carefully crafted such…