2 citations · 4 across the 4 of their papers we have counts for
8 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…