Search Results for author: Seemandhar Jain

Found 6 papers, 0 papers with code

Latent Intrinsics Emerge from Training to Relight

no code implementations31 May 2024 Xiao Zhang, William Gao, Seemandhar Jain, Michael Maire, David. A. Forsyth, Anand Bhattad

Image relighting is the task of showing what a scene from a source image would look like if illuminated differently.

Image Relighting

Improved Convex Decomposition with Ensembling and Boolean Primitives

no code implementations29 May 2024 Vaibhav Vavilala, Florian Kluger, Seemandhar Jain, Bodo Rosenhahn, David Forsyth

Describing a scene in terms of primitives -- geometrically simple shapes that offer a parsimonious but accurate abstraction of structure -- is an established vision problem.

regression Scene Segmentation

Blocks2World: Controlling Realistic Scenes with Editable Primitives

no code implementations7 Jul 2023 Vaibhav Vavilala, Seemandhar Jain, Rahul Vasanth, Anand Bhattad, David Forsyth

We present Blocks2World, a novel method for 3D scene rendering and editing that leverages a two-step process: convex decomposition of images and conditioned synthesis.

Data Augmentation

An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data

no code implementations5 Oct 2021 Seemandhar Jain, Prarthi Jain, Abhishek Srivastava

In this work, we extend our previous work by proposed an efficient iForest based approach for anomaly detection using cube sampling that is effective on streaming data.

Anomaly Detection Event Detection +1

An Energy Efficient Health Monitoring Approach with Wireless Body Area Networks

no code implementations27 Sep 2021 Seemandhar Jain, Prarthi Jain, Prabhat K. Upadhyay, Jules M. Moualeu, Abhishek Srivastava

In addition to being able to handle streaming data, the model works within the resource-constrained environments of an LPU and eliminates the need of transmitting the data to a back-end cloud, ensuring further energy savings.

Anomaly Detection

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