activity
20172021
most citedLearning N:M Fine-grained Structured Sparse Neural Networks From Scratch

74 citations · 81 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation

Ziniu Wan, Zhengjia Li, Maoqing Tian +3

3D human shape and pose estimation is the essential task for human motion analysis, which is widely used in many 3D applications. However, existing methods cannot simultaneously ca…

cs.CV202174 cited

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Aojun Zhou, Yukun Ma, Junnan Zhu +5

Sparsity in Deep Neural Networks (DNNs) has been widely studied to compress and accelerate the models on resource-constrained environments. It can be generally categorized into uns…

cs.CV20201 cited

A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection

Jianbo Liu, Sijie Ren, Yuanjie Zheng +2

Both high-level and high-resolution feature representations are of great importance in various visual understanding tasks. To acquire high-resolution feature maps with high-level s…

cs.CV20202 cited

EfficientFCN: Holistically-guided Decoding for Semantic Segmentation

Jianbo Liu, Junjun He, Jiawei Zhang +2

Both performance and efficiency are important to semantic segmentation. State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (…

cs.CV2020

Learning to Predict Context-adaptive Convolution for Semantic Segmentation

Jianbo Liu, Junjun He, Jimmy S. Ren +2

Long-range contextual information is essential for achieving high-performance semantic segmentation. Previous feature re-weighting methods demonstrate that using global context for…

cs.CV2018

Learning Selfie-Friendly Abstraction from Artistic Style Images

Yicun Liu, Jimmy Ren, Jianbo Liu +2

Artistic style transfer can be thought as a process to generate different versions of abstraction of the original image. However, most of the artistic style transfer operators are…