For this purpose, we propose two networks, i.e., sparse-scale convolutional neural network (SS-CNN) and dense-scale convolutional neural network (DS-CNN). SS-CNN detects human heads with coarse information about the scales in the image. DS-CNN utilizes detection obtained from SS-CNN and ...
This survey aims to provide a comprehensive overview of transformer models with a specific focus on dense prediction. In this survey, we provide a well-rounded view of state-of-the-art transformer-based approaches, explicitly emphasizing pixel-level prediction tasks. We generally consider transformer...
Vision Transformers for Dense Prediction Rene´ Ranftl Alexey Bochkovskiy Intel Labs rene.ranftl@intel.com Vladlen Koltun Abstract We introduce dense prediction transformers, an archi- tecture that leverages vision transformers in place of con- volutional networks as a backbone for dense prediction...
[AAAI 2024] SVDP: Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction - Anonymous-012/SVDP
Sparse R-CNN基于R-CNN框架,其提出了一种一对一稀疏交互的机制,同时借鉴了DETR的可学习候选目标的思想,并且结合二分匹配的标签分配策略和集合预测的形式,实现了端到端目标检测的效果,整个过程无需RPN和NMS。 前言 这段时间的paper不是E2E(End-to-End)就是Transformer,什么都拿Transformer往上套,然后个个都声称自...
在深度学习的时代,cnn[34]已成为占主导地位的对象检测框架,其中包括单级探测器(如SSD [43], RetinaNet [39], FCOS [62], GFL [37, 35], PolarMask [71] and OneNet [55]) and multi-stage detectors (Faster R-CNN [49], Mask R-CNN [21], Cascade R-CNN [4] and Sparse R-CNN [57])和...
Sparse-to-Dense:DepthPredictionfromSparseDepthSamplesandaSingleImageFangchangMa1andSertacKaraman1Abstract—WeconsidertheproblemofdensedepthpredictionfromasparsesetofdepthmeasurementsandasingleRGBimage.Sincedepthestimationfrommonocularimagesaloneisinheren
http://bing.comSparse-To-Dense: Depth Prediction from Sparse Depth Samples and a Single Image字幕版之后会放出,敬请持续关注欢迎加入人工智能机器学习群:556910946,会有视频,资料放送, 视频播放量 368、弹幕量 0、点赞数 1、投硬币枚数 1、收藏人数 2、转发人数 0
英[dens] 美[dɛns] 是什么意思 adj. 密集的,稠密的;浓密的,浓厚的;愚钝的; 双语释义 adj.(形容词) 密集的,稠密的,浓密的closely packed or crowded together 密度大的difficult to see through 愚笨的stupid 英英释义 dense[ dens ] adj. permitting little if any light to pass through because of d...
which pushes the weight of each connection to be binary and the connections to be sparse. The discovered connectivity achieves competitive results on two segmentation datasets, while runs more than three times faster and requires less than half parameters compared to the state-of-the-art methods. ...