Coarctation 发表于 2025-3-21 19:32:36
书目名称Computer Vision -- ECCV 2010影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0234151<br><br> <br><br>书目名称Computer Vision -- ECCV 2010读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0234151<br><br> <br><br>glisten 发表于 2025-3-21 21:09:55
Sequential Non-Rigid Structure-from-Motion with the 3D-Implicit Low-Rank Shape Modelsition takes place. In this paper we propose an incremental approach to the estimation of deformable models. Image frames are processed online in a sequential fashion. The shape is initialised to a rigid model from the first few frames. Subsequently, the problem is formulated as a model based camera宽大 发表于 2025-3-22 01:54:37
http://reply.papertrans.cn/24/2342/234151/234151_3.pngSpirometry 发表于 2025-3-22 06:04:09
http://reply.papertrans.cn/24/2342/234151/234151_4.png树木心 发表于 2025-3-22 11:34:03
http://reply.papertrans.cn/24/2342/234151/234151_5.pngstress-response 发表于 2025-3-22 15:36:55
Euclidean Structure Recovery from Motion in Perspective Image Sequences via Hankel Rank Minimizationtive projection. Existing approaches rely either only on geometrical constraints reflecting the rigid nature of the object, or exploit temporal information by recasting the problem into a nonlinear filtering form. In contrast, here we introduce a new constraint that implicitly exploits the . of thestress-response 发表于 2025-3-22 19:12:14
Exploiting Loops in the Graph of Trifocal Tensors for Calibrating a Network of Cameras epipolar geometries, a parameterization of the graph of trifocal tensors is proposed in which each trifocal tensor is encoded by a 4-vector. The strength of this parameterization is that the homographies relating two adjacent trifocal tensors, as well as the projection matrices depend linearly on treaching 发表于 2025-3-23 01:05:27
http://reply.papertrans.cn/24/2342/234151/234151_8.png浪费时间 发表于 2025-3-23 02:08:23
Conjugate Gradient Bundle Adjustmentmputationally very expensive. An alternative to this approach is to apply the conjugate gradients algorithm in the inner loop. This is appealing since the main computational step of the CG algorithm involves only a simple matrix-vector multiplication with the Jacobian. In this work we improve on the盘旋 发表于 2025-3-23 07:43:34
NF-Features – No-Feature-Features for Representing Non-textured Regionsint detectors do not detect features. As these regions are usually non-textured, stable re-localization in different images with conventional methods is not possible. Therefore, a technique is presented which re-localizes once-detected NF-features using correspondences of regular features. Furthermo