In this paper, an instance level feature representation built upon recent fully convolutional instance-aware segmentation is proposed. The feature is ROI-pooled based on the segmented instance region. So that instances in different sizes and layouts are represented by deep feature in uniform length....
Instance-Level Segmentation with Deep Densely Connected MRFs Our aim is to provide a pixel-level object instance labeling of a monocular image. We build on recent work [27] that trained a convolutional neural net to ... Z Zhang,S Fidler,R Urtasun - 《Arxiv》 被引量: 0发表: 2015年 A ...
saliency detection本身仅仅是检测出显著性的区域,而没有精细到目标个体级别。文章认为个体级别是下一步需要关注和解决的问题,把salient instance segmentation问题分解为3个子任务:1)生成pixel-level的saliency mask(用网络来产生). 2)检测出显著性目标实例的contour,也就是边界检测. 3)找出显著性个体实例,通过产生一些...
object proposal locations, and an instance-level segmentation sub-network that generates the foreground mask of the dominant object instance in each proposal... X Liang,Y Wei,X Shen,... - Computer Vision & Pattern Recognition 被引量: 41发表: 2015年 Integrating instance-level knowledge to see...
For instance, the probability that a given aircraft will be detected at least once while flying any given path through a specified model radar network ... JI Marcum - 《Information Theory Ire Transactions on》 被引量: 903发表: 1960年 Cellular and Network Mechanisms of Slow Oscillatory Activity...
最后作者还提出了一个Render-and-Compare Loss,我认为具体的做法就是通过将上述方法得到的object的3D模型加工(Render也有加工的意思)成2D Segmentation mask/2D Depth map,然后与ground truth的2D Segmentation mask/2D Depth map计算loss,用来进一步精细化输出的结果。同时ground truth的2D Segmentation mask/2D Depth ...
In or- der to exploit rich supervisory signals in the form of 2D annotations like segmentation, we propose a differentiable Render-and-Compare loss that allows 3D shape and pose to be learned with 2D supervision. We evaluate our method on the challenging real-world datasets of Pascal3D+ and ...
使用一个 normal-based graph cut 方法对ScanNet数据集进行mesh的过分割(over-segmentation);相较于2d图像面临遮挡和亮度变化的影响,点云数据中不同物体之间有着明显的边界,此特性非常有益于过分割;最后每一个instance可能会被分割成多个segment。(文中指出:虽然有些属于不同instance的部分会被错误合并到一个segment,...
For each RoI, we have ground-truth 2D segmentation mask Gs and/or 2D depth-map Gd. From the 3D shape and pose prediction of each RoI, we render the corresponding segmentation mask Rs, and depth-map Rd. In addition we have known binary ignore masks Is and Id, which have va- lue of...
4.3. Object Detection and Segmentation Object detection and segmentation are important tasks in computer vision. We evaluate ILM Norm on Mask R- CNN [5] using MS-COCO dataset [17]. All models are trained on the training set for 90,000 with batch size per GPU equal to 2 using 1 GPU ...