Search Results for author:
Found 18 papers, 3 papers with code
Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement
We first propose a facial component guided deep Convolutional Neural Network (CNN) to restore a coarse face image, which is denoted as the base image where the facial component is automatically generated from the input face image.
Stylizing Face Images via Multiple Exemplars
We address the problem of transferring the style of a headshot photo to face images.
Fast Preprocessing for Robust Face Sketch Synthesis
Exemplar-based face sketch synthesis methods usually meet the challenging problem that input photos are captured in different lighting conditions from training photos.
Learning to Hallucinate Face Images via Component Generation and Enhancement
We propose a two-stage method for face hallucination.
3D Hand Pose Tracking and Estimation Using Stereo Matching
This paper demonstrates that the performance of the state-of-the art tracking/estimation algorithms can be maintained with most stereo matching algorithms on the proposed benchmark, as long as the hand segmentation is correct.
RGBD Salient Object Detection via Deep Fusion
Numerous efforts have been made to design different low level saliency cues for the RGBD saliency detection, such as color or depth contrast features, background and color compactness priors.
Ranked #26 on
RGB-D Salient Object Detection
on NJU2K
Real-Time Salient Object Detection With a Minimum Spanning Tree
In this paper, we present a real-time salient object detection system based on the minimum spanning tree.
Ranked #5 on
Video Salient Object Detection
on MCL
(using extra training data)
Semantic Filtering
However, natural photos contain objects of different sizes which cannot be described by a single scale measurement.
Exemplar-Driven Top-Down Saliency Detection via Deep Association
To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects.
Superpixel Hierarchy
Quantitative and qualitative evaluation on a number of computer vision applications was conducted, demonstrating that the proposed method is the top performer.
Deep Colorization
This paper investigates into the colorization problem which converts a grayscale image to a colorful version.
Video Tracking Using Learned Hierarchical Features
The adaptation is conducted in both layers of the deep feature learning module so as to include appearance information of the specific target object.
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
In order to encode the class correlation and class specific information in image representation, we propose a new local feature learning approach named Deep Discriminative and Shareable Feature Learning (DDSFL).
Multimodal Multipart Learning for Action Recognition in Depth Videos
We propose a joint sparse regression based learning method which utilizes the structured sparsity to model each action as a combination of multimodal features from a sparse set of body parts.
Real-Time Part-Based Visual Tracking via Adaptive Correlation Filters
However, the conventional correlation filter based trackers cannot deal with occlusion.
Robust Piecewise-Constant Smoothing: M-Smoother Revisited
In addition, high-quality piecewise-constant smoothing can be achieved via a number of bilateral filtering or guided filtering integrated in the proposed framework.
Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow
We present a fast optical flow algorithm that can handle large displacement motions.
Visual Tracking via Locality Sensitive Histograms
A robust tracking framework based on the locality sensitive histograms is proposed, which consists of two main components: a new feature for tracking that is robust to illumination changes and a novel multi-region tracking algorithm that runs in realtime even with hundreds of regions.
