9 citations · 31 across the 8 of their papers we have counts for
9 papers
Surface Defect Classification in Real-Time Using Convolutional Neural Networks
Selim Arikan, Kiran Varanasi, Didier Stricker
Surface inspection systems are an important application domain for computer vision, as they are used for defect detection and classification in the manufacturing industry. Existing…
Learning Quadrangulated Patches For 3D Shape Processing
Kripasindhu Sarkar, Kiran Varanasi, Didier Stricker
We propose a system for surface completion and inpainting of 3D shapes using generative models, learnt on local patches. Our method uses a novel encoding of height map based local…
DeepHPS: End-to-end Estimation of 3D Hand Pose and Shape by Learning from Synthetic Depth
Jameel Malik, Ahmed Elhayek, Fabrizio Nunnari +4
Articulated hand pose and shape estimation is an important problem for vision-based applications such as augmented reality and animation. In contrast to the existing methods which…
Learning 3D Shapes as Multi-Layered Height-maps using 2D Convolutional Networks
Kripasindhu Sarkar, Basavaraj Hampiholi, Kiran Varanasi +1
We present a novel global representation of 3D shapes, suitable for the application of 2D CNNs. We represent 3D shapes as multi-layered height-maps (MLH) where at each grid locatio…
Fast Feature Extraction with CNNs with Pooling Layers
Christian Bailer, Tewodros Habtegebrial, Kiran varanasi +1
In recent years, many publications showed that convolutional neural network based features can have a superior performance to engineered features. However, not much effort was take…
Fast View Synthesis with Deep Stereo Vision
Tewodros Habtegebrial, Kiran Varanasi, Christian Bailer +1
Novel view synthesis is an important problem in computer vision and graphics. Over the years a large number of solutions have been put forward to solve the problem. However, the la…
HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model
Vladislav Golyanik, Soshi Shimada, Kiran Varanasi +1
Monocular dense 3D reconstruction of deformable objects is a hard ill-posed problem in computer vision. Current techniques either require dense correspondences and rely on motion a…
Learning quadrangulated patches for 3D shape parameterization and completion
Kripasindhu Sarkar, Kiran Varanasi, Didier Stricker
We propose a novel 3D shape parameterization by surface patches, that are oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail on local patches, we learn…
CNN-based Patch Matching for Optical Flow with Thresholded Hinge Embedding Loss
Christian Bailer, Kiran Varanasi, Didier Stricker
Learning based approaches have not yet achieved their full potential in optical flow estimation, where their performance still trails heuristic approaches. In this paper, we presen…