9.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR444 papers
- Institute for High Energy PhysicsES405 papers
- Stanford UniversityUS359 papers
- University of SouthamptonGB359 papers
- University College LondonGB358 papers
- University of MichiganUS356 papers
- Fermi National Accelerator LaboratoryUS350 papers
- University of ChicagoUS344 papers
- Ludwig-Maximilians-Universität MünchenDE323 papers
- University of Illinois Urbana-ChampaignUS315 papers
- Centro de Investigaciones Energéticas, Medioambientales y TecnológicasES312 papers
- The Ohio State UniversityUS305 papers
12 papers · 2 filters
Universal Semi-Supervised Semantic Segmentation
Tarun Kalluri, Girish Varma, Manmohan Chandraker +1
In recent years, the need for semantic segmentation has arisen across several different applications and environments. However, the expense and redundancy of annotation often limit…
C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis
K J Joseph, Arghya Pal, Sailaja Rajanala +1
Generating an image from its description is a challenging task worth solving because of its numerous practical applications ranging from image editing to virtual reality. All exist…
MASON: A Model AgnoStic ObjectNess Framework
K J Joseph, Vineeth N Balasubramanian
This paper proposes a simple, yet very effective method to localize dominant foreground objects in an image, to pixel-level precision. The proposed method 'MASON' (Model-AgnoStic O…
Deep Textured 3D Reconstruction of Human Bodies
Abbhinav Venkat, Sai Sagar Jinka, Avinash Sharma
Recovering textured 3D models of non-rigid human body shapes is challenging due to self-occlusions caused by complex body poses and shapes, clothing obstructions, lack of surface t…
A Deep Learning based Joint Segmentation and Classification Framework for Glaucoma Assesment in Retinal Color Fundus Images
Arunava Chakravarty, Jayanthi Sivswamy
Automated Computer Aided diagnostic tools can be used for the early detection of glaucoma to prevent irreversible vision loss. In this work, we present a Multi-task Convolutional N…
Watch to Edit: Video Retargeting using Gaze
Kranthi Kumar, Moneish Kumar, Vineet Gandhi +1
We present a novel approach to optimally retarget videos for varied displays with differing aspect ratios by preserving salient scene content discovered via eye tracking. Our algor…
A deep learning framework for segmentation of retinal layers from OCT images
Karthik Gopinath, Samrudhdhi B Rangrej, Jayanthi Sivaswamy
Segmentation of retinal layers from Optical Coherence Tomography (OCT) volumes is a fundamental problem for any computer aided diagnostic algorithm development. This requires prepr…
Efficient Semantic Segmentation using Gradual Grouping
Nikitha Vallurupalli, Sriharsha Annamaneni, Girish Varma +3
Deep CNNs for semantic segmentation have high memory and run time requirements. Various approaches have been proposed to make CNNs efficient like grouped, shuffled, depth-wise sepa…
Distribution-Aware Binarization of Neural Networks for Sketch Recognition
Ameya Prabhu, Vishal Batchu, Sri Aurobindo Munagala +2
Deep neural networks are highly effective at a range of computational tasks. However, they tend to be computationally expensive, especially in vision-related problems, and also hav…
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data
Arghya Pal, Vineeth N Balasubramanian
Paucity of large curated hand-labeled training data for every domain-of-interest forms a major bottleneck in the deployment of machine learning models in computer vision and other…
Unsupervised Learning of Face Representations
Samyak Datta, Gaurav Sharma, C. V. Jawahar
We present an approach for unsupervised training of CNNs in order to learn discriminative face representations. We mine supervised training data by noting that multiple faces in th…
HWNet v2: An Efficient Word Image Representation for Handwritten Documents
Praveen Krishnan, C. V. Jawahar
We present a framework for learning an efficient holistic representation for handwritten word images. The proposed method uses a deep convolutional neural network with traditional…