Search Results for author:
Found 39 papers, 17 papers with code
HDRSplat: Gaussian Splatting for High Dynamic Range 3D Scene Reconstruction from Raw Images
However, with the exception of RawNeRF, all prior 3DGS and NeRF-based methods rely on 8-bit tone-mapped Low Dynamic Range (LDR) images for scene reconstruction.
GAURA: Generalizable Approach for Unified Restoration and Rendering of Arbitrary Views
In this paper, we propose a generalizable neural rendering method that can perform high-fidelity novel view synthesis under several degradations.
Stereo-Knowledge Distillation from dpMV to Dual Pixels for Light Field Video Reconstruction
Dual pixels contain disparity cues arising from the defocus blur.
MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
Passive Snapshot Coded Aperture Dual-Pixel RGB-D Imaging
Our resulting CADS imaging system demonstrates improvement of >1. 5dB PSNR in all-in-focus (AIF) estimates and 5-6% in depth estimation quality over naive DP sensing for a wide range of aperture settings.
OpEnCam: Lensless Optical Encryption Camera
OpEnCam encrypts the incoming light before capturing it using the modulating ability of optical masks.
Spectrum-inspired Low-light Image Translation for Saliency Detection
Saliency detection methods are central to several real-world applications such as robot navigation and satellite imagery.
Acela: Predictable Datacenter-level Maintenance Job Scheduling
While it is tempting to use prior machine learning techniques for predicting job duration, we find that the structure of the maintenance job scheduling problem creates a unique challenge.
Towards Realistic Underwater Dataset Generation and Color Restoration
This can be attributed to the fact that synthetic data cannot accurately represent real conditions.
LWGNet: Learned Wirtinger Gradients for Fourier Ptychographic Phase Retrieval
Fourier Ptychographic Microscopy (FPM) is an imaging procedure that overcomes the traditional limit on Space-Bandwidth Product (SBP) of conventional microscopes through computational means.
Synthesizing Light Field Video from Monocular Video
Hence, we propose a self-supervised learning-based algorithm for LF video reconstruction from monocular videos.
Restoring Extremely Dark Images in Real Time
We propose a new deep learning architecture for extreme low-light single image restoration, which is exceptionally lightweight, remarkably fast, and produces a restoration that is perceptually at par with state-of-the-art computationally intense models.
V-DESIRR: Very Fast Deep Embedded Single Image Reflection Removal
Our method processes the corrupted image in two stages, a Low Scale Sub-network (LSSNet) to process the lowest scale and a Progressive Inference (PI) stage to process all the higher scales.
SeLFVi: Self-Supervised Light-Field Video Reconstruction From Stereo Video
We propose a self-supervised learning-based algorithm for LF video reconstruction from stereo video.
Towards Fast and Light-Weight Restoration of Dark Images
However, doing the bulk of computations in the LR space causes artifacts in the restored image.
A Unified Framework for Compressive Video Recovery from Coded Exposure Techniques
Most recently, a Coded-2-Bucket camera has been proposed that can acquire two compressed measurements in a single exposure, unlike previously proposed coded exposure techniques, which can acquire only a single measurement.
FlatNet: Towards Photorealistic Scene Reconstruction from Lensless Measurements
Lensless imaging has emerged as a potential solution towards realizing ultra-miniature cameras by eschewing the bulky lens in a traditional camera.
Video Reconstruction by Spatio-Temporal Fusion of Blurred-Coded Image Pair
The input to our algorithm is a fully-exposed and coded image pair.
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results
The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration.
Deep Atrous Guided Filter for Image Restoration in Under Display Cameras
In this work, we present Deep Atrous Guided Filter (DAGF), a two-stage, end-to-end approach for image restoration in UDC systems.
Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks
One of the important parameters for the assessment of glaucoma is optic nerve head (ONH) evaluation, which usually involves depth estimation and subsequent optic disc and cup boundary extraction.
Pyramidal Edge-maps and Attention based Guided Thermal Super-resolution
Guided super-resolution (GSR) of thermal images using visible range images is challenging because of the difference in the spectral-range between the images.
Optimal HDR and Depth from Dual Cameras
Finally, we present for the first time a stereo HDR dataset consisting of dense ISO and exposure stack captured from a smartphone dual camera.
Harnessing Multi-View Perspective of Light Fields for Low-Light Imaging
The proposed L3Fnet not only performs the necessary visual enhancement of each LF view but also preserves the epipolar geometry across views.
multi-patch aggregation models for resampling detection
Images captured nowadays are of varying dimensions with smartphones and DSLR's allowing users to choose from a list of available image resolutions.
Unsupervised Single Image Underwater Depth Estimation
We evaluate and compare our method both quantitatively and qualitatively on various underwater images with diverse attenuation and scattering conditions and show that our method produces state-of-the-art results for unsupervised depth estimation from a single underwater image.
Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation
Glaucoma is a serious ocular disorder for which the screening and diagnosis are carried out by the examination of the optic nerve head (ONH).
Neural Decoder for Topological Codes using Pseudo-Inverse of Parity Check Matrix
Our final decoder is independent of the noise model and achieves a threshold of $10 \%$.
A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections
Here, we present a unified learning framework that can reconstruct LF from a variety of multiplexing schemes with minimal number of coded images as input.
Photorealistic Image Reconstruction from Hybrid Intensity and Event based Sensor
Event sensors output a stream of asynchronous brightness changes (called ``events'') at a very high temporal rate.
Phase retrieval for Fourier Ptychography under varying amount of measurements
For the low overlap case we show that a supervised deep learning technique using an autoencoder generator is a good choice for solving the Fourier ptychography problem.
Dynamic Vision Sensors for Human Activity Recognition
We propose to use the various slices (such as $x-y$, $x-t$, and $y-t$) of the DVS video as a feature map for HAR and denote them as Motion Maps.
Solving Inverse Computational Imaging Problems using Deep Pixel-level Prior
On the other hand, a more flexible approach would be to learn a deep generative model once and then use it as a signal prior for solving various inverse problems.
Learning Light Field Reconstruction from a Single Coded Image
We propose to do this in three stages 1) reconstruction of center view from the coded image 2) estimating disparity map from the coded image and center view 3) warping center view using the disparity to generate light field.
Data Driven Coded Aperture Design for Depth Recovery
To address this drawback we propose a data driven approach for learning the optimal aperture pattern to recover depth map from a single coded image.
Compressive Image Recovery Using Recurrent Generative Model
Reconstruction of signals from compressively sensed measurements is an ill-posed problem.
Spatial Phase-Sweep: Increasing temporal resolution of transient imaging using a light source array
Transient imaging or light-in-flight techniques capture the propagation of an ultra-short pulse of light through a scene, which in effect captures the optical impulse response of the scene.
A Framework for the Analysis of Computational Imaging Systems with Practical Applications
Unfortunately, a detailed analysis of CI has proven to be a challenging problem because performance depends equally on three components: (1) the optical multiplexing, (2) the noise characteristics of the sensor, and (3) the reconstruction algorithm.
Large-Scale Matrix Factorization with Missing Data under Additional Constraints
We further demonstrate the effectiveness of the proposed algorithm in solving the affine SfM problem, non-rigid SfM and photometric stereo problems.
