文件名称：ECCV2018目标检测论文
文件大小：35.38MB
文件格式：ZIP
更新时间：2021-11-08 04:03:36
object detec 目标检测 物体检测 深度学习
ECCV2018最新目标检测（物体检测）论文全集，是研究计算机视觉深度学习必看论文。
【文件预览】：
ECCV2018
----Xin_Li_Contour_Knowledge_Transfer_ECCV_2018_paper.pdf(1.24MB)
----Acquisition of Localization Confidence for Accurate Object Detection.pdf(1.55MB)
----Kemal_Oksuz_Localization_Recall_Precision_ECCV_2018_paper.pdf(620KB)
----NIKITA_DVORNIK_Modeling_Visual_Context_ECCV_2018_paper.pdf(2.08MB)
----Unsupervised Hard Example Mining from Videos for Improved Object Detection.pdf(1.61MB)
----Hongyu_Xu_Deep_Regionlets_for_ECCV_2018_paper.pdf(495KB)
----Visual-Inertial Object Detection and Mapping.pdf(1.08MB)
----Yi_Wei_Quantization_Mimic_Towards_ECCV_2018_paper.pdf(1.19MB)
----Zero-Shot Object Detection.pdf(745KB)
----Reverse Attention for Salient Object Detection.pdf(1.85MB)
----Tao_Kong_Deep_Feature_Pyramid_ECCV_2018_paper.pdf(3.13MB)
----SOD-MTGAN - Small Object Detection via Multi-Task Generative Adversarial Network.pdf(1.66MB)
----*g_Li_DetNet_Design_Backbone_ECCV_2018_paper.pdf(1.21MB)
----Salient Objects in Clutter - Bringing Salient Object Detection to the Foreground.pdf(1.25MB)
----Yunchao_Wei_TS2C_Tight_Box_ECCV_2018_paper.pdf(2.16MB)
----Objects that Sound.pdf(1.45MB)
----Seung-Wook_Kim_Parallel_Feature_Pyramid_ECCV_2018_paper.pdf(2.05MB)
----ML-LocNet - Improving Object Localization with Multi-view Learning Network.pdf(1.16MB)
----Zhe_Chen_Context_Refinement_for_ECCV_2018_paper.pdf(956KB)
----Xiaolin_Zhang_Self-produced_Guidance_for_ECCV_2018_paper.pdf(927KB)
----Jiayuan_Gu_Learning_Region_Features_ECCV_2018_paper.pdf(1.39MB)
----Weakly Supervised Region Proposal Network.pdf(941KB)
----Hei_Law_CornerNet_Detecting_Objects_ECCV_2018_paper.pdf(2.01MB)
----Chang_Liu_Linear_Span_Network_ECCV_2018_paper.pdf(965KB)
----Songtao_Liu_Receptive_Field_Block_ECCV_2018_paper.pdf(928KB)
----Zero-Annotation Object Detection with Web.pdf(519KB)
----Krishna_Kumar_Singh_Transferring_Common-Sense_Knowledge_ECCV_2018_paper.pdf(2.91MB)
----Kim_SAN_Learning_Relationship_ECCV_2018_paper.pdf(1.74MB)