CV Code | 计算机视觉开源周报20191001期
CV Code | 计算机视觉开源周报20191001期
本图出自OpenVSLAM
总结了过去一周新出的计算机视觉开源代码。
ICCV 2019 临近，不少论文和相应代码公布，也包括其中的WorkShop的工作。
涵盖的方向包括视觉SLAM、基于标记的SLAM、3D 重建、视线跟踪、植物虫害图像检测识别、人体姿态估计、视频目标分割、语义分割等。
SLAM
OpenVSLAM: A Versatile Visual SLAM Framework
Shinya Sumikura, Mikiya Shibuya, Ken Sakurada
ACM Multimedia 2019 Open Source Software Competition
https://arxiv.org/abs/1910.01122v1
https://github.com/xdspacelab/openvslam
SLAM
TagSLAM: Robust SLAM with Fiducial Markers
Bernd Pfrommer, Kostas Daniilidis
https://arxiv.org/abs/1910.00679v1
https://berndpfrommer.github.io/tagslam_web
3D 重建
Learning Continuous 3D Reconstructions for Geometrically Aware Grasping
Mark Van der Merwe, Qingkai Lu, Balakumar Sundaralingam, Martin Matak, Tucker Hermans
ICRA 2020
https://arxiv.org/abs/1910.00983v1
视线跟踪
RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking
Aayush K.Chaudhary, Rakshit Kothari, Manoj Acharya, Shusil Dangi, Nitinraj Nair, Reynold Bailey, Christopher Kanan, Gabriel Diaz, Jeff B. Pelz
ICCV 2019 Workshop OpenEDS Semantic Segmentation Challenge for Eye images
https://arxiv.org/abs/1910.00694v1
https://bitbucket.org/eye-ush/ritnet/
植物虫害图像检测与识别
Research on insect pest image detection and recognition based on bio-inspired methods
Loris Nanni, Gianluca Maguolo, Fabio Pancino
https://arxiv.org/abs/1910.00296v1
https://github.com/LorisNanni/
机器人推动行为数据集
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video
Maria Bauza, Ferran Alet, Yen-Chen Lin, Tomas Lozano-Perez, Leslie P. Kaelbling, Phillip Isola, Alberto Rodriguez
IROS 2019
https://arxiv.org/abs/1910.00618v1
https://web.mit.edu/mcube/omnipush-dataset/
基于胶囊网络的半监督视频目标分割
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
Kevin Duarte, Yogesh S Rawat, Mubarak Shah
ICCV 2019
https://arxiv.org/abs/1910.00132v1
https://github.com/KevinDuarte/CapsuleVOS
物体 6D 姿态估计
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation
Kartik Gupta, Lars Petersson, Richard Hartley
ICCV Workshop on Recovering 6D Object Pose, 2019
https://arxiv.org/abs/1909.13476v1
https://github.com/kartikgupta-at-anu/CullNet
用于语义分割的最大方差损失域适应
Domain Adaptation for Semantic Segmentation with Maximum Squares Loss
Minghao Chen, Hongyang Xue, Deng Cai
ICCV 2019
https://arxiv.org/abs/1909.13589v1
https://github.com/ZJULearning/MaxSquareLoss
单网络全人体的姿态估计方法
Single-Network Whole-Body Pose Estimation
Gines Hidalgo, Yaadhav Raaj, Haroon Idrees, Donglai Xiang, Hanbyul Joo, Tomas Simon, Yaser Sheikh
ICCV 2019
https://arxiv.org/abs/1909.13423v1
https://github.com/CMU-Perceptual-Computing-Lab/openpose_train
OpenPose 升级，CMU提出首个单网络全人体姿态估计网络，速度大幅提高
EdgeCNN：CNN用于边缘计算
EdgeCNN: Convolutional Neural Network Classification Model with small inputs for Edge Computing
Shunzhi Yang, Zheng Gong, Kai Ye, Yungen Wei, Zheng Huang, Zhenhua Huang
https://arxiv.org/abs/1909.13522v1
https://github.com/yangshunzhi1994/EdgeCNN
视频目标分割 | 基于可微分掩膜匹配方法
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun
ICCV 2019
https://arxiv.org/abs/1909.12471v1
https://github.com/ZENGXH/DMM_Net
实时多目标跟踪
Towards Real-Time Multi-Object Tracking
Zhongdao Wang, Liang Zheng, Yixuan Liu, Shengjin Wang
https://arxiv.org/abs/1909.12605v1
https://github.com/Zhongdao/Towards-Realtime-MOT
3D 人体姿态与形状重建的学习方法
Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop
Nikos Kolotouros, Georgios Pavlakos, Michael J. Black, Kostas Daniilidis
ICCV 2019
https://arxiv.org/abs/1909.12828v1
https://seas.upenn.edu/~nkolot/projects/spin
一种可学习的树滤波器，用于结构保持的特征变换，嵌入到语义分割网络中，有效改进了分割精度
Learnable Tree Filter for Structure-preserving Feature Transform
Lin Song, Yanwei Li, Zeming Li, Gang Yu, Hongbin Sun, Jian Sun, Nanning Zheng
NeurIPS-2019
https://arxiv.org/abs/1909.12513v1
https://github.com/StevenGrove/TreeFilter-Torch