53 citations · 232 across the 44 of their papers we have counts for
13 papers · 1 filter
Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma
Binaural audio gives the listener an immersive experience and can enhance augmented and virtual reality. However, recording binaural audio requires specialized setup with a dummy h…
Beyond Image to Depth: Improving Depth Prediction using Echoes
Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma
We address the problem of estimating depth with multi modal audio visual data. Inspired by the ability of animals, such as bats and dolphins, to infer distance of objects with echo…
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
Siddharth Srivastava, Gaurav Sharma
We propose simple yet effective improvements in point representations and local neighborhood graph construction within the general framework of graph neural networks (GNNs) for 3D…
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles
Siddharth Srivastava, Frederic Jurie, Gaurav Sharma
We address the problem of 3D object detection from 2D monocular images in autonomous driving scenarios. We propose to lift the 2D images to 3D representations using learned neural…
DeepPoint3D: Learning Discriminative Local Descriptors using Deep Metric Learning on 3D Point Clouds
Siddharth Srivastava, Brejesh Lall
Learning local descriptors is an important problem in computer vision. While there are many techniques for learning local patch descriptors for 2D images, recently efforts have bee…
Enhanced Characterness for Text Detection in the Wild
Aarushi Agrawal, Prerana Mukherjee, Siddharth Srivastava +1
Text spotting is an interesting research problem as text may appear at any random place and may occur in various forms. Moreover, ability to detect text opens the horizons for impr…
Object Classification using Ensemble of Local and Deep Features
Siddharth Srivastava, Prerana Mukherjee, Brejesh Lall +1
In this paper we propose an ensemble of local and deep features for object classification. We also compare and contrast effectiveness of feature representation capability of variou…
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Li Yi, Lin Shao, Manolis Savva +47
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…
Drought Stress Classification using 3D Plant Models
Siddharth Srivastava, Swati Bhugra, Brejesh Lall +1
Quantification of physiological changes in plants can capture different drought mechanisms and assist in selection of tolerant varieties in a high throughput manner. In this contex…
3D Binary Signatures
Siddharth Srivastava, Brejesh Lall
In this paper, we propose a novel binary descriptor for 3D point clouds. The proposed descriptor termed as 3D Binary Signature (3DBS) is motivated from the matching efficiency of t…
Large Scale Novel Object Discovery in 3D
Siddharth Srivastava, Gaurav Sharma, Brejesh Lall
We present a method for discovering never-seen-before objects in 3D point clouds obtained from sensors like Microsoft Kinect. We generate supervoxels directly from the point cloud…
Benchmarking KAZE and MCM for Multiclass Classification
Siddharth Srivastava, Prerana Mukherjee, Brejesh Lall
In this paper, we propose a novel approach for feature generation by appropriately fusing KAZE and SIFT features. We then use this feature set along with Minimal Complexity Machine…
SIFT Vs SURF: Quantifying the Variation in Transformations
Siddharth Srivastava
This paper studies the robustness of SIFT and SURF against different image transforms (rigid body, similarity, affine and projective) by quantitatively analyzing the variations in…