Search Results for author:
Found 21 papers, 5 papers with code
Boundary Attention: Learning to Localize Boundaries under High Noise
We present a differentiable model that infers explicit boundaries, including curves, corners and junctions, using a mechanism that we call boundary attention.
Polarization Multi-Image Synthesis with Birefringent Metasurfaces
In contrast to previous work on incoherent opto-electronic filtering that can realize only one spatial filter, our approach can realize a continuous family of filters from a single capture, with filters being selected from the family by adjusting the post-capture digital summation weights.
Eclipse: Disambiguating Illumination and Materials using Unintended Shadows
We present a method based on differentiable Monte Carlo ray tracing that uses images of an object to jointly recover its spatially-varying materials, the surrounding illumination environment, and the shapes of the unseen light occluders who inadvertently cast shadows upon it.
Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
Neural Radiance Fields (NeRF) is a popular view synthesis technique that represents a scene as a continuous volumetric function, parameterized by multilayer perceptrons that provide the volume density and view-dependent emitted radiance at each location.
Level Set Binocular Stereo with Occlusions
Localizing stereo boundaries and predicting nearby disparities are difficult because stereo boundaries induce occluded regions where matching cues are absent.
StegaPos: Preventing Unwanted Crops and Replacements with Imperceptible Positional Embeddings
We present a learned, spatially-varying steganography system that allows detecting when and how images have been altered by cropping, splicing or inpainting after publication.
Field of Junctions: Extracting Boundary Structure at Low SNR
We introduce a bottom-up model for simultaneously finding many boundary elements in an image, including contours, corners and junctions.
Level Set Stereo for Cooperative Grouping with Occlusion
We introduce an energy and level-set optimizer that improves boundaries by encoding the essential geometry of occlusions: The spatial extent of an occlusion must equal the amplitude of the disparity jump that causes it.
Unique Geometry and Texture from Corresponding Image Patches
We present a sufficient condition for recovering unique texture and viewpoints from unknown orthographic projections of a flat texture process.
Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset
Scene motion, multiple reflections, and sensor noise introduce artifacts in the depth reconstruction performed by time-of-flight cameras.
Focal Track: Depth and Accommodation With Oscillating Lens Deformation
The focal track sensor is a monocular and computationally efficient depth sensor that is based on defocus controlled by a liquid membrane lens.
Toward Perceptually-Consistent Stereo: A Scanline Study
Two types of information exist in a stereo pair: correlation (matching) and decorrelation (half-occlusion).
Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective
We show that Sinkhorn-Knopp is equivalent to an Expectation-Maximization (EM) algorithm of learning a Gaussian mixture model of the image patches.
Hot or Not: Exploring Correlations Between Appearance and Temperature
In this paper we explore interactions between the appearance of an outdoor scene and the ambient temperature.
On the Appearance of Translucent Edges
We also discuss the existence of shape and material metamers, or combinations of distinct shape or material parameters that generate the same edge profile.
Low-level Vision by Consensus in a Spatial Hierarchy of Regions
We introduce a multi-scale framework for low-level vision, where the goal is estimating physical scene values from image data---such as depth from stereo image pairs.
Monte Carlo non local means: Random sampling for large-scale image filtering
In particular, our error probability bounds show that, at any given sampling ratio, the probability for MCNLM to have a large deviation from the original NLM solution decays exponentially as the size of the image or database grows.
Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images
To produce images that are suitable for display, tone-mapping is widely used in digital cameras to map linear color measurements into narrow gamuts with limited dynamic range.
From Shading to Local Shape
We develop a framework for extracting a concise representation of the shape information available from diffuse shading in a small image patch.
Finding Group Interactions in Social Clutter
We consider the problem of finding distinctive social interactions involving groups of agents embedded in larger social gatherings.
Dimensionality Reduction Using the Sparse Linear Model
We propose an approach for linear unsupervised dimensionality reduction, based on the sparse linear model that has been used to probabilistically interpret sparse coding.
