34 citations · 60 across the 13 of their papers we have counts for
13 papers
Quality-Aware Network for Human Parsing
Lu Yang, Qing Song, Zhihui Wang +3
How to estimate the quality of the network output is an important issue, and currently there is no effective solution in the field of human parsing. In order to solve this problem,…
PcmNet: Position-Sensitive Context Modeling Network for Temporal Action Localization
Xin Qin, Hanbin Zhao, Guangchen Lin +3
Temporal action localization is an important and challenging task that aims to locate temporal regions in real-world untrimmed videos where actions occur and recognize their classe…
DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency
Jiehong Lin, Zewei Wei, Zhihao Li +3
Category-level 6D object pose and size estimation is to predict full pose configurations of rotation, translation, and size for object instances observed in single, arbitrary views…
Renovating Parsing R-CNN for Accurate Multiple Human Parsing
Lu Yang, Qing Song, Zhihui Wang +5
Multiple human parsing aims to segment various human parts and associate each part with the corresponding instance simultaneously. This is a very challenging task due to the divers…
DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data
Wei Yin, Xinlong Wang, Chunhua Shen +5
We present a method for depth estimation with monocular images, which can predict high-quality depth on diverse scenes up to an affine transformation, thus preserving accurate shap…
Indices Matter: Learning to Index for Deep Image Matting
Hao Lu, Yutong Dai, Chunhua Shen +1
We show that existing upsampling operators can be unified with the notion of the index function. This notion is inspired by an observation in the decoding process of deep image mat…
Index Network
Hao Lu, Yutong Dai, Chunhua Shen +1
We show that existing upsampling operators can be unified using the notion of the index function. This notion is inspired by an observation in the decoding process of deep image ma…
Dynamic Topology Adaptation Based on Adaptive Link Selection Algorithms for Distributed Estimation
S. Xu, R. C. de Lamare, H. V. Poor
This paper presents adaptive link selection algorithms for distributed estimation and considers their application to wireless sensor networks and smart grids. In particular, exhaus…
Distributed Compressed Estimation for Wireless Sensor Networks Based on Compressive Sensing
S. Xu, R. C. de Lamare, H. V. Poor
This letter proposes a novel distributed compressed estimation scheme for sparse signals and systems based on compressive sensing techniques. The proposed scheme consists of compre…
Distributed Low-Rank Estimation Based on Joint Iterative Optimization in Wireless Sensor Networks
S. Xu, R. C. de Lamare, H. V. Poor
This paper proposes a novel distributed reduced--rank scheme and an adaptive algorithm for distributed estimation in wireless sensor networks. The proposed distributed scheme is ba…
Adaptive Link Selection Strategies for Distributed Estimation in Wireless Sensor Networks
Songcen Xu, Rodrigo C. de Lamare, H. Vincent Poor
In this work, we propose adaptive link selection strategies for distributed estimation in diffusion-type wireless networks. We develop an exhaustive search-based link selection alg…
Dynamic Topology Adaptation and Distributed Estimation for Smart Grids
S. Xu, R. C. de Lamare, H. V. Poor
This paper presents new dynamic topology adaptation strategies for distributed estimation in smart grids systems. We propose a dynamic exhaustive search--based topology adaptation…
Distributed conjugate gradient strategies for parameter estimation over sensor networks
Songcen Xu, Rodrigo C. de Lamare
This paper presents distributed adaptive algorithms based on the conjugate gradient (CG) method for distributed networks. Both incremental and diffusion adaptive solutions are all…