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Found 7 papers, 4 papers with code
Neural Spline Fields for Burst Image Fusion and Layer Separation
Each photo in an image burst can be considered a sample of a complex 3D scene: the product of parallax, diffuse and specular materials, scene motion, and illuminant variation.
Shakes on a Plane: Unsupervised Depth Estimation from Unstabilized Photography
Modern mobile burst photography pipelines capture and merge a short sequence of frames to recover an enhanced image, but often disregard the 3D nature of the scene they capture, treating pixel motion between images as a 2D aggregation problem.
GenSDF: Two-Stage Learning of Generalizable Signed Distance Functions
The first stage uses an episodic training scheme to simulate training on unlabeled data and meta-learns initial shape priors.
The Implicit Values of A Good Hand Shake: Handheld Multi-Frame Neural Depth Refinement
Modern smartphones can continuously stream multi-megapixel RGB images at 60Hz, synchronized with high-quality 3D pose information and low-resolution LiDAR-driven depth estimates.
Centimeter-Wave Free-Space Time-of-Flight Imaging
In this work, we close this gap and propose a computational imaging method for all-optical free-space correlation before photo-conversion that achieves micron-scale depth resolution with robustness to surface reflectance and ambient light with conventional silicon intensity sensors.
Mask-ToF: Learning Microlens Masks for Flying Pixel Correction in Time-of-Flight Imaging
We introduce Mask-ToF, a method to reduce flying pixels (FP) in time-of-flight (ToF) depth captures.
Duodepth: Static Gesture Recognition Via Dual Depth Sensors
Static gesture recognition is an effective non-verbal communication channel between a user and their devices; however many modern methods are sensitive to the relative pose of the user's hands with respect to the capture device, as parts of the gesture can become occluded.
