Search results with tag "Ob ject"
Dynamic DETR: End-to-End Object Detection With Dynamic ...
openaccess.thecvf.comObject detection aims at predicting a set of bounding boxes and category labels for each object of interest. Mod- ... typical feature pyramid that is widely used in modern ob-ject detectors, and relatively low performance at detecting ... detection by first introducing Region Proposal Networks (RPN) to extract region features and then applying ...
Generalized Intersection over Union: A Metric and A Loss ...
giou.stanford.edupopular object detection benchmarks such as PASCAL VOC and MS COCO. 1. Introduction Bounding box regression is one of the most fundamental components in many 2D/3D computer vision tasks. Tasks such as object localization, multiple object detection, ob-ject tracking and instance level segmentation rely on ac-curate bounding box regression.
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Abstract arXiv:2012.09161v2 [cs.CV] 1 Apr 2021
arxiv.organ independent implicit neural representation for each ob-ject, recent works share a function space for the implicit representations of different objects. Typically, a latent space is defined where each object corresponds to a latent code. The latent code can be obtained by optimization with an auto-decoder [34,6]. For example, Park et al. [34 ...
Tech report (v5) - arXiv
arxiv.orgimage classification and object detection. This paper is the first to show that a CNN can lead to dramatically higher ob-ject detection performance on PASCAL VOC as compared to systems based on simpler HOG-like features. To achieve this result, we focused on two problems: localizing objects with a deep network and training a high-capacity model
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arXiv:1711.11585v2 [cs.CV] 20 Aug 2018
arxiv.orging images. Using semantic segmentation methods, we can transform images into a semantic label domain, edit the ob-jects in the label domain, and then transform them back to the image domain. This method also gives us new tools for higher-level image editing, e.g., adding objects to images or changing the appearance of existing objects.
Siamese Instance Search for Tracking
arxiv.orgalso known as particular object retrieval, is related to ob-ject tracking, especially when localized [22, 43]. The most popular paradigm is based on matching local im-age descriptors between the query and the candidate im-age [40, 36, 20, 37, 45, 43] and is especially accurate for buildings [36]. Recently, [44] proposed to learn a
The Chinese Wall Security Policy - Purdue University
www.cs.purdue.edub) at the intermediate level, we group all ob-jects which concern the same corporation to-gether into what we will call a company datase~ c) at the highest level, we group together all company datasets whose corporations are i n competition. We will refer to each such group as a conflict of interest class. Associated with each object is the ...
Introduction to Adobe InDesign (2022)
idme-test.ome.ksu.edu(visuals, video, audio, animations) and texts…and place these ob jects into your file (or you can create the artworks and texts simultaneously to the layout design). InDesign . There are numerous right ways to start, continue, and complete the work. …
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arXiv:2004.01888v6 [cs.CV] 19 Oct 2021
arxiv.orgChen et al.,2018b), one-shot trackers which estimate ob-jects and learn re-ID features using a single network have attracted more attention (Wang et al.,2020b;Voigtlaender et al.,2019). For example, Voigtlaender et al. (Voigtlaender et al.,2019) add a re-ID branch to Mask R-CNN to extract a re-ID feature for each proposal (He et al.,2017). It ...
PANet: Few-Shot Image Semantic Segmentation With …
openaccess.thecvf.comin Figure 1. PANet first embeds different foreground ob-jects and background into different prototypes via a shared feature extractor. In this way, each learned prototype is rep-resentative for the corresponding class and meanwhile is sufficiently distinguishable from …