Search Results for author: Rohit Pandey

Found 21 papers, 4 papers with code

One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation

no code implementations19 Feb 2024 Zhixuan Yu, Ziqian Bai, Abhimitra Meka, Feitong Tan, Qiangeng Xu, Rohit Pandey, Sean Fanello, Hyun Soo Park, yinda zhang

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability.

Camera Calibration

MVDD: Multi-View Depth Diffusion Models

no code implementations8 Dec 2023 Zhen Wang, Qiangeng Xu, Feitong Tan, Menglei Chai, Shichen Liu, Rohit Pandey, Sean Fanello, Achuta Kadambi, yinda zhang

State-of-the-art results from extensive experiments demonstrate MVDD's excellent ability in 3D shape generation, depth completion, and its potential as a 3D prior for downstream tasks.

3D Shape Generation Denoising +3

Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and Editing

no code implementations5 Dec 2023 Yushi Lan, Feitong Tan, Di Qiu, Qiangeng Xu, Kyle Genova, Zeng Huang, Sean Fanello, Rohit Pandey, Thomas Funkhouser, Chen Change Loy, yinda zhang

We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility.

Face Model

Controllable Light Diffusion for Portraits

no code implementations CVPR 2023 David Futschik, Kelvin Ritland, James Vecore, Sean Fanello, Sergio Orts-Escolano, Brian Curless, Daniel Sýkora, Rohit Pandey

We introduce light diffusion, a novel method to improve lighting in portraits, softening harsh shadows and specular highlights while preserving overall scene illumination.

Semantic Segmentation

HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences

1 code implementation CVPR 2021 Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Fanello, Ping Tan, yinda zhang

In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses.

GeLaTO: Generative Latent Textured Objects

no code implementations ECCV 2020 Ricardo Martin-Brualla, Rohit Pandey, Sofien Bouaziz, Matthew Brown, Dan B. Goldman

Accurate modeling of 3D objects exhibiting transparency, reflections and thin structures is an extremely challenging problem.

Neural Light Transport for Relighting and View Synthesis

1 code implementation9 Aug 2020 Xiuming Zhang, Sean Fanello, Yun-Ta Tsai, Tiancheng Sun, Tianfan Xue, Rohit Pandey, Sergio Orts-Escolano, Philip Davidson, Christoph Rhemann, Paul Debevec, Jonathan T. Barron, Ravi Ramamoorthi, William T. Freeman

In particular, we show how to fuse previously seen observations of illuminants and views to synthesize a new image of the same scene under a desired lighting condition from a chosen viewpoint.

Learning Illumination from Diverse Portraits

no code implementations5 Aug 2020 Chloe LeGendre, Wan-Chun Ma, Rohit Pandey, Sean Fanello, Christoph Rhemann, Jason Dourgarian, Jay Busch, Paul Debevec

We present a learning-based technique for estimating high dynamic range (HDR), omnidirectional illumination from a single low dynamic range (LDR) portrait image captured under arbitrary indoor or outdoor lighting conditions.

Lighting Estimation

Portrait Shadow Manipulation

1 code implementation18 May 2020 Xuaner Cecilia Zhang, Jonathan T. Barron, Yun-Ta Tsai, Rohit Pandey, Xiuming Zhang, Ren Ng, David E. Jacobs

We propose a way to explicitly encode facial symmetry and show that our dataset and training procedure enable the model to generalize to images taken in the wild.

State of the Art on Neural Rendering

no code implementations8 Apr 2020 Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Kalyan Sunkavalli, Ricardo Martin-Brualla, Tomas Simon, Jason Saragih, Matthias Nießner, Rohit Pandey, Sean Fanello, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Eli Shechtman, Dan B. Goldman, Michael Zollhöfer

Neural rendering is a new and rapidly emerging field that combines generative machine learning techniques with physical knowledge from computer graphics, e. g., by the integration of differentiable rendering into network training.

BIG-bench Machine Learning Image Generation +2

Breaking hypothesis testing for failure rates

1 code implementation13 Jan 2020 Rohit Pandey, Yingnong Dang, Gil Lapid Shafriri, Murali Chintalapati, Aerin Kim

Next, we compare the performance of the rate test to a version of the Wald test customized to the Negative Binomial point process and find it to perform very similarly while being much more general and versatile.

Point Processes Two-sample testing

Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning

no code implementations CVPR 2019 Rohit Pandey, Anastasia Tkach, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Ricardo Martin-Brualla, Andrea Tagliasacchi, George Papandreou, Philip Davidson, Cem Keskin, Shahram Izadi, Sean Fanello

The key insight is to leverage previously seen "calibration" images of a given user to extrapolate what should be rendered in a novel viewpoint from the data available in the sensor.

Neural Rerendering in the Wild

no code implementations CVPR 2019 Moustafa Meshry, Dan B. Goldman, Sameh Khamis, Hugues Hoppe, Rohit Pandey, Noah Snavely, Ricardo Martin-Brualla

Starting from internet photos of a tourist landmark, we apply traditional 3D reconstruction to register the photos and approximate the scene as a point cloud.

3D Reconstruction

LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering

no code implementations12 Nov 2018 Ricardo Martin-Brualla, Rohit Pandey, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Julien Valentin, Sameh Khamis, Philip Davidson, Anastasia Tkach, Peter Lincoln, Adarsh Kowdle, Christoph Rhemann, Dan B. Goldman, Cem Keskin, Steve Seitz, Shahram Izadi, Sean Fanello

We take the novel approach to augment such real-time performance capture systems with a deep architecture that takes a rendering from an arbitrary viewpoint, and jointly performs completion, super resolution, and denoising of the imagery in real-time.

Denoising Super-Resolution

Optimizing Waiting Thresholds Within A State Machine

no code implementations8 Oct 2018 Rohit Pandey, Yifan Chang, Cameron White, Gaurav Jagtiani, Aerin Young Kim, Gil Lapid Shafriri, Sathya Singh

When a node goes unresponsive for more than a set threshold, FC intervenes and reboots the node.

Egocentric 6-DoF Tracking of Small Handheld Objects

no code implementations16 Apr 2018 Rohit Pandey, Pavel Pidlypenskyi, Shuoran Yang, Christine Kaeser-Chen

Virtual and augmented reality technologies have seen significant growth in the past few years.

Deep Secure Encoding: An Application to Face Recognition

no code implementations14 Jun 2015 Rohit Pandey, Yingbo Zhou, Venu Govindaraju

In this paper we present Deep Secure Encoding: a framework for secure classification using deep neural networks, and apply it to the task of biometric template protection for faces.

Face Recognition General Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.