203 citations · 678 across the 20 of their papers we have counts for
11 papers · 1 filter
Super Diffusion for Salient Object Detection
Peng Jiang, Zhiyi Pan, Nuno Vasconcelos +2
One major branch of saliency object detection methods is diffusion-based which construct a graph model on a given image and diffuse seed saliency values to the whole graph by a dif…
Image Smoothing via Unsupervised Learning
Qingnan Fan, Jiaolong Yang, David Wipf +2
Image smoothing represents a fundamental component of many disparate computer vision and graphics applications. In this paper, we present a unified unsupervised (label-free) learni…
Deep Video-Based Performance Cloning
Kfir Aberman, Mingyi Shi, Jing Liao +3
We present a new video-based performance cloning technique. After training a deep generative network using a reference video capturing the appearance and dynamics of a target actor…
Neural Material: Learning Elastic Constitutive Material and Damping Models from Sparse Data
Bin Wang, Paul Kry, Yuanmin Deng +3
The accuracy and fidelity of deformation simulations are highly dependent upon the underlying constitutive material model. Commonly used linear or nonlinear constitutive material m…
Decouple Learning for Parameterized Image Operators
Qingnan Fan, Dongdong Chen, Lu Yuan +3
Many different deep networks have been used to approximate, accelerate or improve traditional image operators, such as image smoothing, super-resolution and denoising. Among these…
SketchyScene: Richly-Annotated Scene Sketches
Changqing Zou, Qian Yu, Ruofei Du +6
We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level. The dat…