Search Results for author:
Found 56 papers, 19 papers with code
Multi-frame denoising of high speed optical coherence tomography data using inter-frame and intra-frame priors
Optical coherence tomography (OCT) is an important interferometric diagnostic technique which provides cross-sectional views of the subsurface microstructure of biological tissues.
Fourier Analysis on Transient Imaging with a Multifrequency Time-of-Flight Camera
A transient image is the optical impulse response of a scene which visualizes light propagation during an ultra-short time interval.
Transparent Object Reconstruction via Coded Transport of Intensity
Capturing and understanding visual signals is one of the core interests of computer vision.
Blind Optical Aberration Correction by Exploring Geometric and Visual Priors
Furthermore, by investigating the visual artifacts of aberration degenerated images captured by consumer-level cameras, the non-uniform distribution of sharpness across color channels and the image lattice is exploited as visual priors, resulting in a novel strategy to utilize the guidance from the sharpest channel and local image regions to improve the overall performance and robustness.
Light Field From Micro-Baseline Image Pair
We first introduce a disparity assisted phase based synthesis (DAPS) strategy that can integrate disparity infor- mation into the phase term of a reference image to warp it to its close neighbor views.
Scene-adaptive Coded Apertures Imaging
Firstly, we capture the scene with a pinhole and analyze the scene content to determine primary edge orientations.
Sampling-based Causal Inference in Cue Combination and its Neural Implementation
Although the Bayesian causal inference model explains the problem of causal inference in cue combination successfully, how causal inference in cue combination could be implemented by neural circuits, is unclear.
Robust Non-Rigid Motion Tracking and Surface Reconstruction Using L0 Regularization
We present a new motion tracking method to robustly reconstruct non-rigid geometries and motions from single view depth inputs captured by a consumer depth sensor.
Fast and High Quality Highlight Removal from A Single Image
Specifically, this paper derives a normalized dichromatic model for the pixels with identical diffuse color: a unit circle equation of projection coefficients in two subspaces that are orthogonal to and parallel with the illumination, respectively.
Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient
Fourier ptychographic microscopy (FPM) is a novel computational coherent imaging technique for high space-bandwidth product imaging.
FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras
We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera.
Light Field Reconstruction Using Deep Convolutional Network on EPI
In this paper, we take advantage of the clear texture structure of the epipolar plane image (EPI) in the light field data and model the problem of light field reconstruction from a sparse set of views as a CNN-based angular detail restoration on EPI.
Experimental comparison of single-pixel imaging algorithms
Various algorithms have been proposed for SPI reconstruction, including the linear correlation methods, the alternating projection method (AP), and the compressive sensing based methods.
BodyFusion: Real-Time Capture of Human Motion and Surface Geometry Using a Single Depth Camera
To reduce the ambiguities of the non-rigid deformation parameterization on the surface graph nodes, we take advantage of the internal articulated motion prior for human performance and contribute a skeleton-embedded surface fusion (SSF) method.
Structured Illumination in Spatial-Orientational Hyperspace
The dipole nature of chromophore is important for both super-resolution microscopy and imaging molecular structure, which is nevertheless neglected in most microscopies, even including structured illumination microscopy (SIM) with polarized excitations.
Optics
DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor
We further propose a joint motion tracking method based on the double layer representation to enable robust and fast motion tracking performance.
A PID Controller Approach for Stochastic Optimization of Deep Networks
We first reveal the intrinsic connections between SGD-Momentum and PID based controller, then present the optimization algorithm which exploits the past, current, and change of gradients to update the network parameters.
Rank Minimization for Snapshot Compressive Imaging
We further investigate the special structure of the sampling process in SCI to tackle the computational workload and memory issues in SCI reconstruction.
HybridFusion: Real-Time Performance Capture Using a Single Depth Sensor and Sparse IMUs
We propose a light-weight and highly robust real-time human performance capture method based on a single depth camera and sparse inertial measurement units (IMUs).
Capture Dense: Markerless Motion Capture Meets Dense Pose Estimation
Specifically, we first introduce a novel markerless motion capture method that can take advantage of dense parsing capability provided by the dense pose detector.
DeepHuman: 3D Human Reconstruction from a Single Image
We propose DeepHuman, an image-guided volume-to-volume translation CNN for 3D human reconstruction from a single RGB image.
SimulCap : Single-View Human Performance Capture with Cloth Simulation
This paper proposes a new method for live free-viewpoint human performance capture with dynamic details (e. g., cloth wrinkles) using a single RGBD camera.
Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition
There are two main problems in label inference: how to measure the confidence of the unlabeled data and how to generalize the classifier.
Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imaging
Snapshot compressive imaging (SCI) aims to capture the high-dimensional (usually 3D) images using a 2D sensor (detector) in a single snapshot.
SurfaceNet+: An End-to-end 3D Neural Network for Very Sparse Multi-view Stereopsis
Furthermore, the latter problem is handled via a multi-scale strategy that consequently refines the recovered geometry around the region with the repeating pattern.
PaMIR: Parametric Model-Conditioned Implicit Representation for Image-based Human Reconstruction
To overcome the limitations of regular 3D representations, we propose Parametric Model-Conditioned Implicit Representation (PaMIR), which combines the parametric body model with the free-form deep implicit function.
Ranked #2 on
3D Human Reconstruction
on CAPE
Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit
Here, we propose an optoelectronic reconfigurable computing paradigm by constructing a diffractive processing unit (DPU) that can efficiently support different neural networks and achieve a high model complexity with millions of neurons.
Deep Implicit Templates for 3D Shape Representation
Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power.
PoNA: Pose-guided Non-local Attention for Human Pose Transfer
In each block, we propose a pose-guided non-local attention (PoNA) mechanism with a long-range dependency scheme to select more important regions of image features to transfer.
Plug-and-Play Algorithms for Video Snapshot Compressive Imaging
On the other hand, applying SCI to large-scale problems (HD or UHD videos) in our daily life is still challenging and one of the bottlenecks lies in the reconstruction algorithm.
Light Field Reconstruction Using Convolutional Network on EPI and Extended Applications
The main problem in direct reconstruction on the EPI involves an information asymmetry between the spatial and angular dimensions, where the detailed portion in the angular dimensions is damaged by undersampling.
Universal and Flexible Optical Aberration Correction Using Deep-Prior Based Deconvolution
High quality imaging usually requires bulky and expensive lenses to compensate geometric and chromatic aberrations.
DeepMultiCap: Performance Capture of Multiple Characters Using Sparse Multiview Cameras
We propose DeepMultiCap, a novel method for multi-person performance capture using sparse multi-view cameras.
Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors
Human volumetric capture is a long-standing topic in computer vision and computer graphics.
10-mega pixel snapshot compressive imaging with a hybrid coded aperture
Towards this end, snapshot compressive imaging (SCI) was proposed as a promising solution to improve the throughput of imaging systems by compressive sampling and computational reconstruction.
Imaging dynamics beneath turbid media via parallelized single-photon detection
Noninvasive optical imaging through dynamic scattering media has numerous important biomedical applications but still remains a challenging task.
Computational Imaging and Artificial Intelligence: The Next Revolution of Mobile Vision
Signal capture stands in the forefront to perceive and understand the environment and thus imaging plays the pivotal role in mobile vision.
A Dual Sensor Computational Camera for High Quality Dark Videography
In this paper, we propose to build a dual-sensor camera to additionally collect the photons in NIR wavelength, and make use of the correlation between RGB and near-infrared (NIR) spectrum to perform high-quality reconstruction from noisy dark video pairs.
All-optical graph representation learning using integrated diffractive photonic computing units
Photonic neural networks perform brain-inspired computations using photons instead of electrons that can achieve substantially improved computing performance.
INFWIDE: Image and Feature Space Wiener Deconvolution Network for Non-blind Image Deblurring in Low-Light Conditions
In terms of algorithm design, INFWIDE proposes a two-branch architecture, which explicitly removes noise and hallucinates saturated regions in the image space and suppresses ringing artifacts in the feature space, and integrates the two complementary outputs with a subtle multi-scale fusion network for high quality night photograph deblurring.
Optical Neural Ordinary Differential Equations
Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance.
SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data
To address this issue, we firstly derive a mathematical explanation for INR's spectrum concentration property and an analytical insight on the design of INR based compressor.
TINC: Tree-structured Implicit Neural Compression
In this paper, we propose a Tree-structured Implicit Neural Compression (TINC) to conduct compact representation for local regions and extract the shared features of these local representations in a hierarchical manner.
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units
Here, we propose the EEG opto-processor based on diffractive photonic computing units (DPUs) to effectively process the extracranial and intracranial EEG signals and perform epileptic seizure detection.
DarkVision: A Benchmark for Low-light Image/Video Perception
In this paper, we contribute the first multi-illuminance, multi-camera, and low-light dataset, named DarkVision, serving for both image enhancement and object detection.
CUTS: Neural Causal Discovery from Irregular Time-Series Data
Causal discovery from time-series data has been a central task in machine learning.
Hi Sheldon! Creating Deep Personalized Characters from TV Shows
To support this novel task, we further collect a character centric multimodal dialogue dataset, named Deep Personalized Character Dataset (DPCD), from TV shows.
Super-NeRF: View-consistent Detail Generation for NeRF super-resolution
Given multi-view low-resolution images, Super-NeRF constructs a consistency-controlling super-resolution module to generate view-consistent high-resolution details for NeRF.
SHoP: A Deep Learning Framework for Solving High-order Partial Differential Equations
Solving partial differential equations (PDEs) has been a fundamental problem in computational science and of wide applications for both scientific and engineering research.
ImmersiveNeRF: Hybrid Radiance Fields for Unbounded Immersive Light Field Reconstruction
This paper proposes a hybrid radiance field representation for unbounded immersive light field reconstruction which supports high-quality rendering and aggressive view extrapolation.
PARF: Primitive-Aware Radiance Fusion for Indoor Scene Novel View Synthesis
This paper proposes a method for fast scene radiance field reconstruction with strong novel view synthesis performance and convenient scene editing functionality.
Lightweight High-Speed Photography Built on Coded Exposure and Implicit Neural Representation of Videos
In this work, by leveraging classical coded exposure imaging technique and emerging implicit neural representation for videos, we tactfully embed the motion direction cues into the blurry image during the imaging process and develop a novel self-recursive neural network to sequentially retrieve the latent video sequence from the blurry image utilizing the embedded motion direction cues.
An Event-Oriented Diffusion-Refinement Method for Sparse Events Completion
Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth.
Context-aware Talking Face Video Generation
To achieve this, we provide a two-stage and cross-modal controllable video generation pipeline, taking facial landmarks as an explicit and compact control signal to bridge the driving audio, talking context and generated videos.
Event-Enhanced Snapshot Compressive Videography at 10K FPS
To unlock the potential of conventional snapshot compressive videography, we propose a novel hybrid "intensity+event" imaging scheme by incorporating an event camera into a video SCI setup.
