Search Results for author:
Found 9 papers, 4 papers with code
RegHEC: Hand-Eye Calibration via Simultaneous Multi-view Point Clouds Registration of Arbitrary Object
RegHEC is a registration-based hand-eye calibration technique with no need for accurate calibration rig but arbitrary available objects, applicable for both eye-in-hand and eye-to-hand cases.
Automatic Facial Skin Feature Detection for Everyone
We present an automatic facial skin feature detection method that works across a variety of skin tones and age groups for selfies in the wild.
HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration
Our experimental results show that the proposed method is able to perform high-quality restoration for unconstrained underwater images without any supervision.
TB-Net: A Three-Stream Boundary-Aware Network for Fine-Grained Pavement Disease Segmentation
It consists of three streams fusing the low-level spatial and the high-level contextual representations as well as the detailed boundary information.
Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences
In this paper, we propose a new task of machine translation (MT), which is based on no parallel sentences but can refer to a ground-truth bilingual dictionary.
FREEtree: A Tree-based Approach for High Dimensional Longitudinal Data With Correlated Features
This paper proposes FREEtree, a tree-based method for high dimensional longitudinal data with correlated features.
Query-Conditioned Three-Player Adversarial Network for Video Summarization
Video summarization plays an important role in video understanding by selecting key frames/shots.
Dilated Temporal Relational Adversarial Network for Generic Video Summarization
Specifically, DTR-GAN learns a dilated temporal relational generator and a discriminator with three-player loss in an adversarial manner.
Unsupervised Object-Level Video Summarization with Online Motion Auto-Encoder
Unsupervised video summarization plays an important role on digesting, browsing, and searching the ever-growing videos every day, and the underlying fine-grained semantic and motion information (i. e., objects of interest and their key motions) in online videos has been barely touched.
