Titlebook: Computer-Aided Design and Computer Graphics; 18th International C Shi-Min Hu,Yiyu Cai,Paul Rosin Conference proceedings 2024 The Editor(s)

心胸开阔

,Spatial-Temporal Consistency Constraints for Chinese Sign Language Synthesis,, directly splicing or combining video clips may result in video jumping problems. To this end, this paper proposes a novel spatial-temporal consistency constraints (STCC) approach for sign synthesis, which enhances the authenticity and acceptability of the synthesized video by generating intermedia

Benign

,An Easy-to-Build Modular Robot Implementation of Chain-Based Physical Transformation for STEM Educalications in a variety of industries. In this paper, we presented EasySRRobot, a low-cost, easy-to-build self-reconfigurable modular robot, to realize the automatic transformation across different configurations, and overcomes the limitation of existing transformation methods requiring manual involv

轿车

千篇一律

,Color-Correlated Texture Synthesis for Hybrid Indoor Scenes,e predicts theme color for each room using a GAN-based method, before generating texture maps using combinatorial optimization. We consider constraints on material selection, color correlation, and color palette matching. Our experiments show the pipeline’s ability to produce pleasing and harmonious

Deference

tendinitis

NeRF Synthesis with Shading Guidance,h only sparse views given. However, utilizing NeRF to reconstruct real-world scenes requires images from different viewpoints, which limits its practical application. This problem can be even more pronounced for large scenes. In this paper, we introduce a new task called NeRF synthesis that utilizes

meritorious

,Multi-scale Hybrid Transformer Network with Grouped Convolutional Embedding for Automatic Cephalomee challenge of developing automatic cephalometric detection methods that are both precise and cost-effective for detecting as many landmarks as possible. Although current deep learning-based approaches have attained high accuracy, they have limitations in detecting landmarks that lack distinct textu

手势

,ZDL: Zero-Shot Degradation Factor Learning for Robust and Efficient Image Enhancement,abeled training data and are limited by the data distribution and application scenarios. To address these limitations, inspired by Hadamard theory, we propose a Zero-shot Degradation Factor Learning (ZDL) for robust and efficient image enhancement, which also could be extended to various harsh scena

性满足

,Self-supervised Contrastive Feature Refinement for Few-Shot Class-Incremental Learning,ard to capture the underlying patterns and traits of the few-shot classes. To meet the challenges, we propose a Self-supervised Contrastive Feature Refinement (SCFR) framework which tackles the FSCIL issue from three aspects. Firstly, we employ a self-supervised learning framework to make the networ

爱管闲事

https://doi.org/10.1007/978-981-99-9666-73D vision; Bio-CAD and Nano-CAD; computer animation; deep learning for graphics; geometric modeling; geom