01 Actual Pain.m4a
size: 7.50 MB
size: N/A
非常棒的evan moor daily系列-原版英语教材-两小无猜网
|- 10 扫描版 Daily Word Problems Math G1-G6 - 0 B
|- 09 Daily_Handwriting_Practice - 0 B
|- 08 Daily Academic VocabularyG2 4 5 6+ - 0 B
|- 07 原版 Daily Science G1-3 - 0 B
|- 06 原版 Daily reading comprehension 1-6+ - 0 B
|- 05 原版 Daily paragraph editing 2-6共五册 - 0 B
|- 04 原版 Daily Math Practice 小学生英语版数学G1-G6 练习册 - 0 B
|- 03 原版 Daily Language Review1-6 共6册 - 0 B
|- 02 原版 Daily Geography Practice 地理G1 G3 练习册 - 0 B
|- 01 原版 Daily 6-trait writing grade 2 4 5 6 英文写作训练 - 0 B
size: N/A
01Paper会员(CV)精读论文专栏资料合集(更新中) - 百度云网盘资源 - 大力盘搜索
|- 30待更新SENet - 0 B
|- 29待更新CenterNet - 0 B
|- 28待更新《Hourglass》 - 0 B
|- 27《CRNN》 - 0 B
|- 26《CTPN Detecting Text in Natural Image with Connectionist Text Proposal Network》 - 0 B
|- 25《Fully-Convolutional Siamese Networks for Object Tracking (SiameseFC) 》 - 0 B
|- 24《GOTURN-Learning to Track at 100 FPS with Deep Regression Networks》 - 0 B
|- 23《FCNT-Visual Tracking with Fully Convolutional Networks 》 - 0 B
|- 22《Online Object Tracking A Benchmark》 - 0 B
|- 21《Linknet Exploiting encoder representations for efficient semantic segmentation》 - 0 B
|- 20《Pyramid scene parsing network》 - 0 B
|- 19《Segnet A deep convolutional encoder-decoder architecture for image segmentation》 - 0 B
|- 18《Deeplab Semantic image segmentation with deep convolutional nets》, - 0 B
|- 17待更新U-Net - 0 B
|- 16《Fully convolutional networks for semantic segmentation》 - 0 B
|- 15 《Facenet A unified embedding for face recognition and clustering(triplet loss)》 - 0 B
|- 14《A Discriminative Feature Learning Approach for Deep Face Recognition(center loss)》 - 0 B
|- 13《Mask R-CNN》 - 0 B
|- 12待更新《Faster R-CNN Towards Real-Time Object Detection with Region Proposal Networks》 - 0 B
|- 11《Region-Based Convolutional Networks for Accurate Object Detection and Segmentation》 - 0 B
|- 10《DSSD》 - 0 B
|- 09《SSD Single Shot MultiBox Detector 》 - 0 B
|- 08待更新《YOLOv3 An Incremental Improvement》 - 0 B
|- 07《You Only Look OnceUnified, Real-Time Object Detection》 - 0 B
|- 06待更新《Focal Loss for Dense Object Detection 》 - 0 B
|- 05《Going deeper with convolutions.》 - 0 B
|- 04《Deep Residual Learning for Image Recognition》 - 0 B
|- 03《Very Deep Convolutional Networks for Large-Scale Image Recognition》 - 0 B
|- 02《ImageNet Classification with Deep Convolutional Neural Network》 - 0 B
|- 01《Deep Learning》 - 0 B
|- 00 若资料和代码错误,请直接联系深度之眼客服更新 - 0 B