Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds (CVPR2022)[paper] Authors: Chenhang He, Ruihuang Li, Shuai Li, Lei Zhang. This project is built on OpenPCDet. Introduction Transformer has demonstrated promising performance in many 2D vision tasks. However, it is cumbersome to compute the self-attention on large-scale point cloud data because point cloud is a long sequence and unevenly distributed in 3D space. To solve this issue, existing methods usually compute self-attention locally by grouping the points […]

OpenDet Expanding Low-Density Latent Regions for Open-Set Object Detection (CVPR2022) Jiaming Han, Yuqiang Ren, Jian Ding, Xingjia Pan, Ke Yan, Gui-Song Xia. arXiv preprint. OpenDet2: OpenDet is implemented based on detectron2. Setup The code is based on detectron2 v0.5. Here is a from-scratch setup script. conda create -n opendet2 python=3.8 -y conda activate opendet2 conda install pytorch=1.8.1 torchvision cudatoolkit=10.1 -c pytorch -y pip install detectron2==0.5 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu101/torch1.8/index.html git clone    

Bu projede YOLOv3-608 modeli kullanılmıştır. Requirements Documentation Yolo ile ilgili detaylı bilgilere bu link üzerinden erişebilirsiniz. Yolov3 modelinin import edilmesi için aşağıdaki dosyalar indirilerek YOLO/Model/ klasörünün içine eklenmelidir. YOLOv3-608 için cfg dosya linki YOLOv3-608 için weights dosya linki OpenCV ve Numpy kütüphanesi kurulumu için: $ pip install opencv-python $ pip install numpy Örnek görüntü ve çıktısı Görüntü Yolov3 ile Çıktı GitHub View    

Acknowledgement We implement our model, BtcDet, based on [OpenPcdet 0.3.0]. Installation Requirements All the codes are tested in the following environment: Install b. Install the dependent libraries as follows: Install the dependent python libraries: pip install -r requirements.txt Install the SparseConv library, we use the implementation from [spconv]. If you use PyTorch 1.1, then make sure you install the spconv v1.0 with (commit 8da6f96) instead of the latest one. If you use PyTorch 1.3+, then you need to install the […]

The PyTorch code for ACM MM2021 paper “Complementary Trilateral Decoder for Fast and Accurate Salient Object Detection” Python 3.6 Pytorch 1.4+ OpenCV 4.0 Numpy TensorboardX Apex Download the SOD datasets and unzip them into data folder. We implement our method by PyTorch and conduct experiments on a NVIDIA 1080Ti GPU. We adopt pre-trained ResNet-18 and ResNet-50 as backbone networks, which are saved in res folder. We train our method on DUTS-TR and test our method on other datasets. After training, […]