找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur

[復(fù)制鏈接]
樓主: Cleveland
21#
發(fā)表于 2025-3-25 05:42:26 | 只看該作者
22#
發(fā)表于 2025-3-25 10:35:02 | 只看該作者
https://doi.org/10.1007/978-94-6209-221-1aluated on several motion estimation problems, including optical flow and rotational motion. As proof of concept, we also test our framework on 6-DOF estimation by performing the optimisation directly in 3D space.
23#
發(fā)表于 2025-3-25 15:31:12 | 只看該作者
24#
發(fā)表于 2025-3-25 19:39:36 | 只看該作者
D. Dudley Williams BSc, Dip. Ed MSc, PhDation, illumination estimation, as well as inverse kinematics. Comparing to traditional optimization-based methods, we can achieve comparable or better performance while being two to three orders of magnitude faster. Compared to deep learning-based approaches, our model consistently improves the performance on all metrics.
25#
發(fā)表于 2025-3-25 22:01:02 | 只看該作者
26#
發(fā)表于 2025-3-26 02:36:20 | 只看該作者
BLSM: A Bone-Level Skinned Model of the Human Mesh,L-type baseline. Our decoupled bone and shape representation also allows for out-of-box integration with standard graphics packages like Unity, facilitating full-body AR effects and image-driven character animation. Additional results and demos are available from the project webpage: ..
27#
發(fā)表于 2025-3-26 07:33:14 | 只看該作者
Associative Alignment for Few-Shot Image Classification, on four standard datasets and three backbones demonstrate that combining our centroid-based alignment loss results in absolute accuracy improvements of 4.4%, 1.2%, and 6.2% in 5-shot learning over the state of the art for object recognition, fine-grained classification, and cross-domain adaptation, respectively.
28#
發(fā)表于 2025-3-26 10:40:35 | 只看該作者
View-Invariant Probabilistic Embedding for Human Pose,higher accuracy when retrieving similar poses across different camera views, in comparison with 2D-to-3D pose lifting models. We also demonstrate the effectiveness of applying our embeddings to view-invariant action recognition and video alignment. Our code is available at ..
29#
發(fā)表于 2025-3-26 14:33:00 | 只看該作者
Contact and Human Dynamics from Monocular Video,oving quantitative measures of both kinematic and dynamic plausibility. We demonstrate our method on character animation and pose estimation tasks on dynamic motions of dancing and sports with complex contact patterns.
30#
發(fā)表于 2025-3-26 18:10:23 | 只看該作者
Few-Shot Scene-Adaptive Anomaly Detection, each target scene. We propose a meta-learning based approach for solving this new problem; extensive experimental results demonstrate the effectiveness of our proposed method. All codes are released in ..
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-10 16:57
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
益阳市| 米泉市| 稻城县| 诸城市| 台前县| 景宁| 思南县| 武川县| 英山县| 衡东县| 襄城县| 承德县| 册亨县| 岑溪市| 辽阳县| 怀宁县| 五台县| 天峨县| 浑源县| 疏勒县| 平邑县| 迁安市| 札达县| 鹤壁市| 台湾省| 南通市| 达日县| 利辛县| 彩票| 宁国市| 宁陕县| 扶沟县| 板桥市| 鄂托克前旗| 深州市| 浠水县| 临沭县| 康乐县| 南投市| 正阳县| 南雄市|