Dynamic Fluid Surface Reconstruction Using Deep Neural Network
Authors: Simron Thapa, Nianyi Li, Jinwei Ye Description: Recovering the dynamic fluid surface is a long-standing challenging problem in computer vision. Most existing image-based methods require multiple views or a dedicated imaging system. Here we present a learning-based single-image approach for 3D fluid surface reconstruction. Specifically, we design a deep neural network that estimates the depth and normal maps of a fluid surface by analyzing the refractive distortion of a reference background image. D
12 views
14
4
4 months ago 00:05:09 91
Persian Yoga (Pahlavani) - The way of Warriors
4 months ago 00:00:23 1
Jesus Christus | JoJo’s Bizarre Adventure | Steel Ball Run | 120Fps Edit
4 months ago 00:06:07 74
Audio Imperia | FLUID WOODS | Walkthrough
4 months ago 00:16:33 38
💦🏀 CREATE FLUID NIKE LOGO AESTHETICS WITH STICKERS 🏀💦 INSPIRED BY VINCENT SCHWENK - BLENDER TUTORIAL
4 months ago 00:12:45 1
Create Beautiful Seascape Painting with Two BASIC Acrylic Pouring Techniques: Flip Cup & Swipe
4 months ago 00:14:06 1
MAGICAL Black and White Feathers: Acrylic Pouring Split Cup Technique
4 months ago 00:00:23 1
High-Speed Imaging of Shotgun Pattern Development
4 months ago 00:06:27 21
Why Is Nobody Talking About This 3D Platform
4 months ago 00:39:35 1
Will Haider Ackermann Transform Tom Ford’s Legacy?