キャプチャデータを越境する物理ベースアニメーションの研究

早大学位記番号:新7515早稲田大

放射線照射によるSiCダイオードの粒子検出特性の変化

電気通信大学200

Automatic Dance Generation System Considering Sign Language Information

In recent years, thanks to the development of 3DCG animation editing tools (e.g. MikuMikuDance), a lot of 3D character dance animation movies are created by amateur users. However it is very difficult to create choreography from scratch without any technical knowledge. Shiratori et al. [2006] produced the dance automatic generation system considering rhythm and intensity of dance motions. However each segment is selected randomly from database, so the generated dance motion has no linguistic or emotional meanings. Takano et al. [2010] produced a human motion generation system considering motion labels. However they use simple motion labels like “running” or “jump”, so they cannot generate motions that express emotions. In reality, professional dancers make choreography based on music features or lyrics in music, and express emotion or how they feel in music. In our work, we aim at generating more emotional dance motion easily. Therefore, we use linguistic information in lyrics, and generate dance motion. In this paper, we propose the system to generate the sign dance motion from continuous sign language motion based on lyrics of music. This system could help the deaf to listen to music as visualized music application

Automatic Sign Dance Synthesis from Gesture-based Sign Language

Automatic dance synthesis has become more and more popular due to the increasing demand in computer games and animations. Existing research generates dance motions without much consideration for the context of the music. In reality, professional dancers make choreography according to the lyrics and music features. In this research, we focus on a particular genre of dance known as sign dance, which combines gesture-based sign language with full body dance motion. We propose a system to automatically generate sign dance from a piece of music and its corresponding sign gesture. The core of the system is a Sign Dance Model trained by multiple regression analysis to represent the correlations between sign dance and sign gesture/music, as well as a set of objective functions to evaluate the quality of the sign dance. Our system can be applied to music visualization, allowing people with hearing difficulties to understand and enjoy music

EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling

We propose EMAGE, a framework to generate full-body human gestures from audio and masked gestures, encompassing facial, local body, hands, and global movements. To achieve this, we first introduce BEAT2 (BEAT-SMPLX-FLAME), a new mesh-level holistic co-speech dataset. BEAT2 combines a MoShed SMPL-X body with FLAME head parameters and further refines the modeling of head, neck, and finger movements, offering a community-standardized, high-quality 3D motion captured dataset. EMAGE leverages masked body gesture priors during training to boost inference performance. It involves a Masked Audio Gesture Transformer, facilitating joint training on audio-to-gesture generation and masked gesture reconstruction to effectively encode audio and body gesture hints. Encoded body hints from masked gestures are then separately employed to generate facial and body movements. Moreover, EMAGE adaptively merges speech features from the audio's rhythm and content and utilizes four compositional VQ-VAEs to enhance the results' fidelity and diversity. Experiments demonstrate that EMAGE generates holistic gestures with state-of-the-art performance and is flexible in accepting predefined spatial-temporal gesture inputs, generating complete, audio-synchronized results. Our code and dataset are available https://pantomatrix.github.io/EMAGE/Comment: Fix typos; Conflict of Interest Disclosure; CVPR Camera Ready; Project Page: https://pantomatrix.github.io/EMAGE

Real Life Study of Lenvatinib Therapy for Hepatocellular Carcinoma: RELEVANT Study

Introduction: In the REFLECT trial, lenvatinib was found to be noninferior compared to sorafenib in terms of overall survival. Here, we analyze the effects of lenvatinib in the real-life experience of several centers across the world and identify clinical factors that could be significantly associated with survival outcomes. Methods: The study population was derived from retrospectively collected data of HCC patients treated with lenvatinib. The overall cohort included western and eastern populations from 23 center in five countries. Results: We included 1,325 patients with HCC and treated with lenvatinib in our analysis. Median OS was 16.1 months. Overall response rate was 38.5%. Multivariate analysis for OS highlighted that HBsAg positive, NLR >3, and AST >38 were independently associated with poor prognosis in all models. Conversely, NAFLD/NASH-related etiology was independently associated with good prognosis. Median progression-free survival was 6.3 months. Multivariate analysis for progression-free survival revealed that NAFLD/NASH, BCLC, NLR, and AST were independent prognostic factors for progression-free survival. A proportion of 75.2% of patients suffered from at least one adverse effect during the study period. Multivariate analysis exhibited the appearance of decreased appetite grade ≥2 versus grade 0-1 as an independent prognostic factor for worse progression-free survival. 924 patients of 1,325 progressed during lenvatinib (69.7%), and 827 of them had a follow-up over 2 months from the beginning of second-line treatment. From first-line therapy, the longest median OS was obtained with the sequence lenvatinib and immunotherapy (47.0 months), followed by TACE (24.7 months), ramucirumab (21.2 months), sorafenib (15.7 months), regorafenib (12.7 months), and best supportive care (10.8 months). Conclusions: Our study confirms in a large and global population of patients with advanced HCC, not candidates for locoregional treatment the OS reported in the registration study and a high response rate with lenvatinib

Sequential therapies after atezolizumab plus bevacizumab or lenvatinib first-line treatments in hepatocellular carcinoma patients

Introduction: The aim of this retrospective proof-of-concept study was to compare different second-line treatments for patients with hepatocellular carcinoma and progressive disease (PD) after first-line lenvatinib or atezolizumab plus bevacizumab.Materials and methods: A total of 1381 patients had PD at first-line therapy. 917 patients received lenvatinib as first-line treatment, and 464 patients atezolizumab plus bevacizumab as first-line.Results: 49.6% of PD patients received a second-line therapy without any statistical difference in overall survival (OS) between lenvatinib (20.6 months) and atezolizumab plus bev-acizumab first-line (15.7 months; p = 0.12; hazard ratio [HR] = 0.80). After lenvatinib first-line, there wasn't any statistical difference between second-line therapy subgroups (p = 0.27; sorafenib HR: 1; immunotherapy HR: 0.69; other therapies HR: 0.85). Patients who under-went trans-arterial chemo-embolization (TACE) had a significative longer OS than patients who received sorafenib (24.7 versus 15.8 months, p < 0.01; HR = 0.64). After atezolizumab plus bevacizumab first-line, there was a statistical difference between second-line therapy subgroups (p < 0.01; sorafenib HR: 1; lenvatinib HR: 0.50; cabozantinib HR: 1.29; other therapies HR: 0.54). Patients who received lenvatinib (17.0 months) and those who under-went TACE (15.9 months) had a significative longer OS than patients treated with sorafenib (14.2 months; respectively, p = 0.01; HR = 0.45, and p < 0.05; HR = 0.46).Conclusion: Approximately half of patients receiving first-line lenvatinib or atezolizumab plus bevacizumab access second-line treatment. Our data suggest that in patients progressed to atezolizumab plus bevacizumab, the systemic therapy able to achieve the longest survival is lenvatinib, while in patients progressed to lenvatinib, the systemic therapy able to achieve the longest survival is immunotherapy