Search Results for author: Anurag Ranjan

Found 26 papers, 18 papers with code

FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline

no code implementations15 Dec 2023 Chien-Yu Lin, Qichen Fu, Thomas Merth, Karren Yang, Anurag Ranjan

Compared to existing NeRF+SR methods, our pipeline mitigates the SR computing overhead and can be trained up to 23x faster, making it feasible to run on consumer devices such as the Apple MacBook.

Knowledge Distillation Super-Resolution

Probabilistic Speech-Driven 3D Facial Motion Synthesis: New Benchmarks, Methods, and Applications

no code implementations30 Nov 2023 Karren D. Yang, Anurag Ranjan, Jen-Hao Rick Chang, Raviteja Vemulapalli, Oncel Tuzel

While these models can achieve high-quality lip articulation for speakers in the training set, they are unable to capture the full and diverse distribution of 3D facial motions that accompany speech in the real world.

Motion Synthesis

HUGS: Human Gaussian Splats

1 code implementation29 Nov 2023 Muhammed Kocabas, Jen-Hao Rick Chang, James Gabriel, Oncel Tuzel, Anurag Ranjan

We achieve state-of-the-art rendering quality with a rendering speed of 60 FPS while being ~100x faster to train over previous work.

Neural Rendering Novel View Synthesis

Novel-View Acoustic Synthesis from 3D Reconstructed Rooms

1 code implementation23 Oct 2023 Byeongjoo Ahn, Karren Yang, Brian Hamilton, Jonathan Sheaffer, Anurag Ranjan, Miguel Sarabia, Oncel Tuzel, Jen-Hao Rick Chang

Given audio recordings from 2-4 microphones and the 3D geometry and material of a scene containing multiple unknown sound sources, we estimate the sound anywhere in the scene.

Pointersect: Neural Rendering with Cloud-Ray Intersection

no code implementations CVPR 2023 Jen-Hao Rick Chang, Wei-Yu Chen, Anurag Ranjan, Kwang Moo Yi, Oncel Tuzel

Specifically, we train a set transformer that, given a small number of local neighbor points along a light ray, provides the intersection point, the surface normal, and the material blending weights, which are used to render the outcome of this light ray.

Inverse Rendering Neural Rendering +2

FineRecon: Depth-aware Feed-forward Network for Detailed 3D Reconstruction

1 code implementation ICCV 2023 Noah Stier, Anurag Ranjan, Alex Colburn, Yajie Yan, Liang Yang, Fangchang Ma, Baptiste Angles

Recent works on 3D reconstruction from posed images have demonstrated that direct inference of scene-level 3D geometry without test-time optimization is feasible using deep neural networks, showing remarkable promise and high efficiency.

3D Reconstruction

FaceLit: Neural 3D Relightable Faces

no code implementations CVPR 2023 Anurag Ranjan, Kwang Moo Yi, Jen-Hao Rick Chang, Oncel Tuzel

We propose a generative framework, FaceLit, capable of generating a 3D face that can be rendered at various user-defined lighting conditions and views, learned purely from 2D images in-the-wild without any manual annotation.

FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization

4 code implementations ICCV 2023 Pavan Kumar Anasosalu Vasu, James Gabriel, Jeff Zhu, Oncel Tuzel, Anurag Ranjan

To this end, we introduce a novel token mixing operator, RepMixer, a building block of FastViT, that uses structural reparameterization to lower the memory access cost by removing skip-connections in the network.

Image Classification

Naturalistic Head Motion Generation from Speech

no code implementations26 Oct 2022 Trisha Mittal, Zakaria Aldeneh, Masha Fedzechkina, Anurag Ranjan, Barry-John Theobald

Synthesizing natural head motion to accompany speech for an embodied conversational agent is necessary for providing a rich interactive experience.

MobileOne: An Improved One millisecond Mobile Backbone

7 code implementations CVPR 2023 Pavan Kumar Anasosalu Vasu, James Gabriel, Jeff Zhu, Oncel Tuzel, Anurag Ranjan

Furthermore, we show that our model generalizes to multiple tasks - image classification, object detection, and semantic segmentation with significant improvements in latency and accuracy as compared to existing efficient architectures when deployed on a mobile device.

Efficient Neural Network Image Classification +2

NeuMan: Neural Human Radiance Field from a Single Video

1 code implementation23 Mar 2022 Wei Jiang, Kwang Moo Yi, Golnoosh Samei, Oncel Tuzel, Anurag Ranjan

Photorealistic rendering and reposing of humans is important for enabling augmented reality experiences.

LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time

1 code implementation8 Oct 2021 Elvis Nunez, Maxwell Horton, Anish Prabhu, Anurag Ranjan, Ali Farhadi, Mohammad Rastegari

Our models require no retraining, thus our subspace of models can be deployed entirely on-device to allow adaptive network compression at inference time.


Token Pooling in Vision Transformers

no code implementations8 Oct 2021 Dmitrii Marin, Jen-Hao Rick Chang, Anurag Ranjan, Anish Prabhu, Mohammad Rastegari, Oncel Tuzel

Token Pooling is a simple and effective operator that can benefit many architectures.

MorphGAN: One-Shot Face Synthesis GAN for Detecting Recognition Bias

no code implementations9 Dec 2020 Nataniel Ruiz, Barry-John Theobald, Anurag Ranjan, Ahmed Hussein Abdelaziz, Nicholas Apostoloff

Images generated using MorphGAN conserve the identity of the person in the original image, and the provided control over head pose and facial expression allows test sets to be created to identify robustness issues of a facial recognition deep network with respect to pose and expression.

Data Augmentation Face Generation +2

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

2 code implementations ICCV 2021 Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Angel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind

To create our dataset, we leverage a large repository of synthetic scenes created by professional artists, and we generate 77, 400 images of 461 indoor scenes with detailed per-pixel labels and corresponding ground truth geometry.

Multi-Task Learning Scene Understanding +1

Learning Multi-Human Optical Flow

2 code implementations24 Oct 2019 Anurag Ranjan, David T. Hoffmann, Dimitrios Tzionas, Siyu Tang, Javier Romero, Michael J. Black

Therefore, we develop a dataset of multi-human optical flow and train optical flow networks on this dataset.

Optical Flow Estimation

Attacking Optical Flow

1 code implementation ICCV 2019 Anurag Ranjan, Joel Janai, Andreas Geiger, Michael J. Black

In this paper, we extend adversarial patch attacks to optical flow networks and show that such attacks can compromise their performance.

Decoder Optical Flow Estimation +1

Capture, Learning, and Synthesis of 3D Speaking Styles

1 code implementation CVPR 2019 Daniel Cudeiro, Timo Bolkart, Cassidy Laidlaw, Anurag Ranjan, Michael J. Black

To address this, we introduce a unique 4D face dataset with about 29 minutes of 4D scans captured at 60 fps and synchronized audio from 12 speakers.

3D Face Animation Talking Face Generation

Generating 3D faces using Convolutional Mesh Autoencoders

2 code implementations ECCV 2018 Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, Michael J. Black

To address this, we introduce a versatile model that learns a non-linear representation of a face using spectral convolutions on a mesh surface.

3D Face Modelling Face Alignment +1

Learning Human Optical Flow

1 code implementation14 Jun 2018 Anurag Ranjan, Javier Romero, Michael J. Black

Given this, we devise an optical flow algorithm specifically for human motion and show that it is superior to generic flow methods.

Optical Flow Estimation

Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

1 code implementation CVPR 2019 Anurag Ranjan, Varun Jampani, Lukas Balles, Kihwan Kim, Deqing Sun, Jonas Wulff, Michael J. Black

We address the unsupervised learning of several interconnected problems in low-level vision: single view depth prediction, camera motion estimation, optical flow, and segmentation of a video into the static scene and moving regions.

Depth Prediction Monocular Depth Estimation +3

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