Hi @JiaRenChang , Thanks for your excellent work. Could you please release your pretrained model on scene flow dataset?
Our ex- periments in the challenging KITTI scene flow dataset show that we outperform the state-of-the-art by a very large mar- gin, while being 800 times faster. 1. Introduction Scene flow refers to the problem of estimating a three- dimenional motion field from a set of two ...
我按照你的说明,下载了数据集,然后在scene folw上面直接跑(从头开始训练),我训练了10个epoch,loss(我理解的就是EPE)在测试集是3左右。这个EPE是我直接通过跑main.py那个代码电脑上显示的结果,没有用其他代码测试,请问你看这个EPE也是通过这种方式把? 此时我的环境是只用了一块GPU卡,bathc size是3,然后测试的时...
kth-rpl/deflow • • 1 Mar 2021 In this work, we introduce a new large-scale dataset for scene flow estimation derived from corresponding tracked 3D objects, which is ∼1, 000× larger than previous real-world datasets in terms of the number of annotated frames.4...
[42, 43] is a real world scene flow dataset with 142 point cloud pairs, which are all used for testing. The point clouds and GT scene flow are obtained by lifting the annotated disparity maps and optical flow to 3D [22]. As a consequence, the points of the two frames are u...
Results were averaged over the KITTI Scene Flow dataset. KITTI Scene Flow Average number of points: ∼30k E↓ (m) Acc5↑ (%) Acc10↑ (%) θϵ↓ (rad) Time ↓ (s) Graph prior (k=50) 0.225 65.50 70.32 0.277 162.97 Graph prior (k=200) 0.082 84.00 88.45 0.141 310.12 Ours ...
In addition, this paper is the first to address scene flow estimation, while making use of modern depth sensors and monocular appearance images, rather than traditional multi-viewpoint rigs. The algorithm is applied to an existing scene flow dataset, where it achieves comparable results to ...
标题:SceneTracker: Long-term Scene Flow Estimation Network 作者:Bo Wang,Jian Li,Yang Yu,Li Liu,Zhenping Sun,Dewen Hu 机构:国防科技大学 原文链接:https://arxiv.org/abs/2403.19924 代码链接:https://github.com/wwsource/SceneTracker 1. 导读 ...
importosimportzipfilefromtensorflow.keras.preprocessing.imageimportImageDataGenerator# 解压数据集withzipfile.ZipFile('scenes_dataset.zip','r')aszip_ref:zip_ref.extractall('scenes_dataset')# 设置图像数据生成器datagen=ImageDataGenerator(rescale=1.0/255.0)# 加载训练数据train_data=datagen.flow_from_directo...
flow_gt_final_path' dataset/openscene-v1.0/occupancy/mini/log-003-scene-0056/occ_gt/025_occ_final.py OpenScene_openscene-v1.1 ├──meta_datas|├──mini││├──2021.05.12.22.00.38_veh-35_01008_01518.pkl││├──2021.05.12.22.28.35_veh-35_00620_01164.pkl││├──...││└──...