SUNRGBD:由4个RGB-D传感器采集得到,包干10000张图片,规模类似于PASCAL VOC数据集,整个数据集被密集地标注了,包括多边形,带有方向的边框,以及三维空间的布局和类别,适合于场景理解任务。 The Object Segmentation Database (OSD):这个数据库的设计是为了将未知对象从一般的场景中分割出来,即使是在部分遮挡的情况下。类...
2021/August - update some recent papers (IJCV, ICCV2021, IEEE SPL, arXiv) of RGBD semantic segmentation. 2022/January - update some recent papers (TITS, PR, IEEE SPL, arXiv) of RGBD semantic segmentation. 2022/March - update benchmark results on Cityscapes and ScanNet datasets. 2022/April...
Example: To apply ESANet-R34-NBt1D trained on SUNRGB-D to samples from SUNRGB-D, run: #note that the entire first batch is visualized, so larger batch sizes results#in smaller images in the plotpython inference_dataset.py \ --dataset sunrgbd \ --dataset_dir ./datasets/sunrgbd \ --ck...
Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis 摘要:摘要—全面分析场景对于在不同环境中行动的机器人至关重要。语义分割可以增强各种后续任务,例如(语义辅助)人的感知,(语义)自由空间检测,(语义)映射和(语义)导航。在本文中,我们提出了一种高效且强大的RGB-D分割方法,该方法可以使用NVIDIA TensorR...
3D Graph Neural Networks for RGBD Semantic Segmentation 原文章:https://www.yuque.com/lart/papers/wmu47a 动机 主要针对的任务是RGBD语义分割, 不同于往常的RGB图像的语义分割任务, 这里还可以更多的考虑来自D通道的深度信息. 所以对于这类任务需要联合2D外观和3D几何信息来进行联合推理. ...
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling Yang He, Wei-Chen Chiu, Margret Keuper, Mario Fritz STD2P:使用时空数据驱动池化的RGBD语义分割 Abstract:我们提出了一种新的基于超像素的多视图(multi-view)卷积神经网络用于语义图像分割。所提出的网络通过利用来自相同场景的(additiona...
For the SUN-RGBD dataset, we train our model with 50K batch it- erations on the initial learning rates, and fine-tune the non-pretrained layers for TRL for Semantic Segmentation & Depth Estimation 9 30K batch iterations with a learning rate of 0.001. The momentum and weight decay ...
Furthermore, the network parameters can be jointly optimized for boosting the final predictions of depth estimation and semantic segmentation with the coarse-to-fine strategy. Extensive experiments on SUN-RGBD and NYU Depth-V2 datasets demonstrate state-of-the-art performance of the proposed unified ...
因此,为了验证该方法的有效性,作者在三个室内RGB-D benchmark上进行了实验:NYU-Depth-V2 (NYUDv2-13 and -40) , SUN-RGBD and Stanford Indoor Dataset (SID) Experiments on Different Datasets NYUDv2 Dataset: SUN-RGBD Dataset: SID Dataset.: Experiments on Different Architectures Ablation Study...
on network performance during training is discussed.The test results on the SUN RGB-D dataset show that compared with other state-ofthe-art semantic segmentation networks,the performance of the network we proposed is outstanding.Finally,the semantic segmentation based on infrared images is explored ...