Search Results for author:
Found 60 papers, 21 papers with code
Learn to Recover Visible Color for Video Surveillance in a Day
In silicon sensors, the interference between visible and near-infrared (NIR) signals is a crucial problem.
Defending Against Physical Adversarial Patch Attacks on Infrared Human Detection
To address this problem, we are the first to investigate defense strategies against adversarial patch attacks on infrared detection, especially human detection.
Beyond Domain Gap: Exploiting Subjectivity in Sketch-Based Person Retrieval
2) Multi-perspective and multi-style.
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling
In recent years, single-frame image super-resolution (SR) has become more realistic by considering the zooming effect and using real-world short- and long-focus image pairs.
MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing
Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results.
Ranked #8 on
Text-based Image Editing
on PIE-Bench
Fooling Polarization-based Vision using Locally Controllable Polarizing Projection
If so, is that possible to realize these adversarial attacks in the physical world, without being perceived by human eyes?
Visibility Constrained Wide-band Illumination Spectrum Design for Seeing-in-the-Dark
Seeing-in-the-dark is one of the most important and challenging computer vision tasks due to its wide applications and extreme complexities of in-the-wild scenarios.
Single Image Deblurring with Row-dependent Blur Magnitude
Image degradation often occurs during fast camera or object movements, regardless of the exposure modes: global shutter (GS) or rolling shutter (RS).
NeRFrac: Neural Radiance Fields through Refractive Surface
We introduce NeRFrac to realize neural novel view synthesis of scenes captured through refractive surfaces, typically water surfaces.
NIR-assisted Video Enhancement via Unpaired 24-hour Data
In this paper, we defend the feasibility and superiority of NIR-assisted low-light video enhancement results by using unpaired 24-hour data for the first time, which significantly eases data collection and improves generalization performance on in-the-wild data.
Rethinking Video Frame Interpolation from Shutter Mode Induced Degradation
Image restoration from various motion-related degradations, like blurry effects recorded by a global shutter (GS) and jello effects caused by a rolling shutter (RS), has been extensively studied.
High-Fidelity Event-Radiance Recovery via Transient Event Frequency
High-fidelity radiance recovery plays a crucial role in scene information reconstruction and understanding.
Polarized Color Image Denoising
Single-chip polarized color photography provides both visual textures and object surface information in one snapshot.
HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design
Adversarial attacks on thermal infrared imaging expose the risk of related applications.
ClipCrop: Conditioned Cropping Driven by Vision-Language Model
Image cropping has progressed tremendously under the data-driven paradigm.
Blur Interpolation Transformer for Real-World Motion from Blur
This paper studies the challenging problem of recovering motion from blur, also known as joint deblurring and interpolation or blur temporal super-resolution.
Towards Real-World Video Deblurring by Exploring Blur Formation Process
We believe the novel realistic synthesis pipeline and the corresponding RAW video dataset can help the community to easily construct customized blur datasets to improve real-world video deblurring performance largely, instead of laboriously collecting real data pairs.
Efficient Video Deblurring Guided by Motion Magnitude
Video deblurring is a highly under-constrained problem due to the spatially and temporally varying blur.
Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance
Existing solutions to this problem estimate a single image sequence without considering the motion ambiguity for each region.
Polarized Color Image Denoising using Pocoformer
Polarized color photography provides both visual textures and object surficial information in one single snapshot.
Learning Adaptive Warping for Real-World Rolling Shutter Correction
This paper proposes the first real-world rolling shutter (RS) correction dataset, BS-RSC, and a corresponding model to correct the RS frames in a distorted video.
Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Feature
In this paper, we investigate using rolling shutter with a global reset feature (RSGR) to restore clean global shutter (GS) videos.
Bringing Rolling Shutter Images Alive with Dual Reversed Distortion
In this paper, instead of two consecutive frames, we propose to exploit a pair of images captured by dual RS cameras with reversed RS directions for this highly challenging task.
Optimal LED Spectral Multiplexing for NIR2RGB Translation
The industry practice for night video surveillance is to use auxiliary near-infrared (NIR) LED diodes, usually centered at 850nm or 940nm, for scene illumination.
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding
Unlike previous methods that mainly focus on closing the domain gap caused by fog -- defogging the foggy images or fogging the clear images, we propose to alleviate the domain gap by considering fog influence and style variation simultaneously.
Ranked #2 on
Domain Adaptation
on Cityscapes-to-FoggyZurich
Physics-based Noise Modeling for Extreme Low-light Photography
Enhancing the visibility in extreme low-light environments is a challenging task.
Ranked #4 on
Image Denoising
on SID SonyA7S2 x100
Real-world Video Deblurring: A Benchmark Dataset and An Efficient Recurrent Neural Network
Real-world video deblurring in real time still remains a challenging task due to the complexity of spatially and temporally varying blur itself and the requirement of low computational cost.
Ranked #30 on
Image Deblurring
on GoPro
(using extra training data)
4D Hyperspectral Photoacoustic Data Restoration With Reliability Analysis
Hyperspectral photoacoustic (HSPA) spectroscopy is an emerging bi-modal imaging technology that is able to show the wavelength-dependent absorption distribution of the interior of a 3D volume.
Event-Based Bispectral Photometry Using Temporally Modulated Illumination
Analysis of bispectral difference plays a critical role in various applications that involve rays propagating in a light absorbing medium.
Learning To Reconstruct High Speed and High Dynamic Range Videos From Events
Event cameras are novel sensors that capture the dynamics of a scene asynchronously.
Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance
Recovering the 3D geometry of a purely texture-less object with generally unknown surface reflectance (e. g. non-Lambertian) is regarded as a challenging task in multi-view reconstruction.
One Ring to Rule Them All: a simple solution to multi-view 3D-Reconstruction of shapes with unknown BRDF via a small Recurrent ResNet
This paper proposes a simple method which solves an open problem of multi-view 3D-Reconstruction for objects with unknown and generic surface materials, imaged by a freely moving camera and a freely moving point light source.
Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes
Since direct application of existing individual rolling shutter correction (RSC) or global shutter deblurring (GSD) methods on RSCD leads to undesirable results due to inherent flaws in the network architecture, we further present the first learning-based model (JCD) for RSCD.
Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB
To reconstruct spectral signals from multi-channel observations, in particular trichromatic RGBs, has recently emerged as a promising alternative to traditional scanning-based spectral imager.
Optical Flow in the Dark
Many successful optical flow estimation methods have been proposed, but they become invalid when tested in dark scenes because low-light scenarios are not considered when they are designed and current optical flow benchmark datasets lack low-light samples.
An Integrated Enhancement Solution for 24-hour Colorful Imaging
The current industry practice for 24-hour outdoor imaging is to use a silicon camera supplemented with near-infrared (NIR) illumination.
A Sparse Representation Based Joint Demosaicing Method for Single-Chip Polarized Color Sensor
Instead of mechanically demosaicing for the multi-channel polarized color image, we further present a sparse representation-based optimization strategy that utilizes chromatic information and polarimetric information to jointly optimize the model.
Hyperspectral City V1.0 Dataset and Benchmark
This document introduces the background and the usage of the Hyperspectral City Dataset and the benchmark.
Stereo relative pose from line and point feature triplets
In this work, we present two minimal solvers for the stereo relative pose.
Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification
An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis.
Illumination-Adaptive Person Re-identification
To demonstrate the illumination issue and to evaluate our model, we construct two large-scale simulated datasets with a wide range of illumination variations.
Coded Illumination and Imaging for Fluorescence Based Classification
The quick detection of specific substances in objects such as produce items via non-destructive visual cues is vital to ensuring the quality and safety of consumer products.
Polarimetric Three-View Geometry
This paper theorizes the connection between polarization and three-view geometry.
Joint Camera Spectral Sensitivity Selection and Hyperspectral Image Recovery
Hyperspectral image (HSI) recovery from a single RGB image has attracted much attention, whose performance has recently been shown to be sensitive to the camera spectral sensitivity (CSS).
Simultaneous 3D Reconstruction for Water Surface and Underwater Scene
This paper presents the first approach for simultaneously recovering the 3D shape of both the wavy water surface and the moving underwater scene.
Deeply Learned Filter Response Functions for Hyperspectral Reconstruction
More interestingly, by considering physical restrictions in the design process, we are able to realize the deeply learned spectral response functions by using modern film filter production technologies, and thus construct data-inspired multispectral cameras for snapshot hyperspectral imaging.
Camera Pose Estimation With Unknown Principal Point
To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization.
Self-Calibrating Polarising Radiometric Calibration
We present a self-calibrating polarising radiometric calibration method.
From RGB to Spectrum for Natural Scenes via Manifold-Based Mapping
Spectral analysis of natural scenes can provide much more detailed information about the scene than an ordinary RGB camera.
A Microfacet-Based Reflectance Model for Photometric Stereo With Highly Specular Surfaces
Recent developments in the field have enabled shape recovery techniques for surfaces of various types, but an effective solution to directly estimating the surface normal in the presence of highly specular reflectance remains elusive.
Making Minimal Solvers for Absolute Pose Estimation Compact and Robust
In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation.
Virtual Blood Vessels in Complex Background using Stereo X-ray Images
We propose a fully automatic system to reconstruct and visualize 3D blood vessels in Augmented Reality (AR) system from stereo X-ray images with bones and body fat.
Image Restoration from Patch-based Compressed Sensing Measurement
A series of methods have been proposed to reconstruct an image from compressively sensed random measurement, but most of them have high time complexity and are inappropriate for patch-based compressed sensing capture, because of their serious blocky artifacts in the restoration results.
Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration
In this paper, we propose an effective method for coded hyperspectral image restoration, which exploits extensive structure sparsity in the hyperspectral image.
A Direct Least-Squares Solution to the PnP Problem With Unknown Focal Length
The advantages of our proposed solution over existing ones are that (i) the objective function is directly built upon the imaging equation, such that all the 3D-to-2D correspondences are treated with balance, and that (ii) the proposed solution is noniterative, in the sense that the stationary points are retrieved by means of standard eigenvalue factorization and the common iterative refinement step is not needed.
Separating Fluorescent and Reflective Components by Using a Single Hyperspectral Image
This paper introduces a novel method to separate fluorescent and reflective components in the spectral domain.
Illumination and Reflectance Spectra Separation of a Hyperspectral Image Meets Low-Rank Matrix Factorization
This paper addresses the illumination and reflectance spectra separation (IRSS) problem of a hyperspectral image captured under general spectral illumination.
Partial Symmetry in Polynomial Systems and its Applications in Computer Vision
Algorithms for solving systems of polynomial equations are key components for solving geometry problems in computer vision.
A General and Simple Method for Camera Pose and Focal Length Determination
In this paper, we revisit the pose determination problem of a partially calibrated camera with unknown focal length, hereafter referred to as the PnPf problem, by using n (n ≥ 4) 3D-to-2D point correspondences.
A Practical Rank-Constrained Eight-Point Algorithm for Fundamental Matrix Estimation
Due to its simplicity, the eight-point algorithm has been widely used in fundamental matrix estimation.
