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

T-cell

書(shū)目名稱Computer Vision – ECCV 2020影響因子(影響力)




書(shū)目名稱Computer Vision – ECCV 2020影響因子(影響力)學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2020網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Computer Vision – ECCV 2020網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2020被引頻次




書(shū)目名稱Computer Vision – ECCV 2020被引頻次學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2020年度引用




書(shū)目名稱Computer Vision – ECCV 2020年度引用學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2020讀者反饋




書(shū)目名稱Computer Vision – ECCV 2020讀者反饋學(xué)科排名

separate

精密

constitutional

,Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and?Objects for 3D Hand Pose Egned (a) to evaluate the influence of both depth and color modalities on 3D hand pose estimation, under the presence or absence of objects; (b) to assess the generalisation abilities .. ?four main axes: shapes, articulations, viewpoints, and objects; (c) to explore the use of a synthetic hand models

鈍劍

Disentangling Multiple Features in Video Sequences Using Gaussian Processes in Variational Autoencothe curvature of the data manifold to improve learning. Our experiments show that the combination of the improved representations with the novel loss function enable MGP-VAE to outperform the baselines in video prediction.

輕彈

輕彈

SACA Net: Cybersickness Assessment of Individual Viewers for VR Content via Graph-Based Symptom Relmulus-response symptom features to effectively predict cybersickness by embedding relational characteristics with graph formulation. For validation, we utilize two public 360-degree video datasets that contain cybersickness scores and physiological signals. Experimental results show that the propose

CHARM

Mindfulness

Know Your Surroundings: Exploiting Scene Information for Object Tracking,re propagated through the sequence and combined with the appearance model output to localize the target. Our network is learned to effectively utilize the scene information by directly maximizing tracking performance on video segments. The proposed approach sets a new state-of-the-art on 3 tracking

Soliloquy