Titlebook: Computational Visual Media; 12th International C Fang-Lue Zhang,Andrei Sharf Conference proceedings 2024 The Editor(s) (if applicable) and

游牧

書目名稱Computational Visual Media影響因子(影響力)




書目名稱Computational Visual Media影響因子(影響力)學(xué)科排名




書目名稱Computational Visual Media網(wǎng)絡(luò)公開度




書目名稱Computational Visual Media網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Visual Media被引頻次




書目名稱Computational Visual Media被引頻次學(xué)科排名




書目名稱Computational Visual Media年度引用




書目名稱Computational Visual Media年度引用學(xué)科排名




書目名稱Computational Visual Media讀者反饋




書目名稱Computational Visual Media讀者反饋學(xué)科排名

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Explore and?Enhance the?Generalization of?Anomaly DeepFake Detection These detection methods primarily enhance generalization by constructing pseudo-fake samples, which involve three main steps: mask generation, source-target preprocessing, and blending. In this paper, we conducted a systematic analysis of some core factors in these steps. Based on the aforementione

ambivalence

CHART

Face Expression Recognition via?Product-Cross Dual Attention and?Neutral-Aware Anchor Losshis task is challenging due to the ambiguities in expressions and also in the diverse poses and occlusions of the head. To handle this challenging task, recent approaches usually rely on attention mechanism to make the network focus on the most critical regions of a face, or apply a consistency loss

仲裁者

煩憂

Single-Video Temporal Consistency Enhancement with?Rolling Guidancelic. However, ensuring the temporal consistency of generated videos is still a challenging problem. Most existing algorithms for temporal consistency enhancement rely on the motion cues from a guidance video to filter the temporally inconsistent video. This paper proposes a novel approach that proce

煩憂

organic-matrix

Silhouette-Based 6D Object Pose Estimationwn objects beyond the training datasets, due to the closed-set assumption and the expensive cost of high-quality annotation. Conversely, traditional methods struggle to achieve accurate pose estimation for texture-less objects. In this work, we propose a silhouette-based 6D object pose estimation me

Physiatrist

Robust Light Field Depth Estimation over?Occluded and?Specular Regionsh range, with the highest level of consistency indicating the correct depth. These methods are based on the photo consistency of Lambertian surface. However, the photo consistency is broken when occlusion and specular reflection occur. In this paper, a new depth estimation algorithm is proposed to s

IRK

Foreground and?Background Separate Adaptive Equilibrium Gradients Loss for?Long-Tail Object Detectioss. However, in the presence of long-tail distribution, the performance is still unsatisfactory. Long-tail data distribution means that a few head classes occupy most of the data, while most of the tail classes are not representative, and tail classes are excessive negatively suppressed during train