시즌 3 논문 and 데이터셋
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Chor-rnn: Kinetic 센서 이용하여 5시간 분량의 현대무용 데이터 채집 후 안무생성
Open
Paper
http://crnkovic-friis.com/research/generative-choreography-using-deep-learning/
Learn to Dance with AIST++: Music Conditioned 3D Dance Generation)
Open
Paper
https://arxiv.org/pdf/2101.08779.pdf
Learn to Dance with AIST++: Music Conditioned 3D Dance Generation)
Open
code
https://github.com/google/aistplusplus_api
Learn to Dance with AIST++: Music Conditioned 3D Dance Generation)
Open
dataset
https://google.github.io/aistplusplus_dataset/
Unifying Vision-and-Language Tasks via Text Generation
Open
Paper
멀티모달 모델
https://arxiv.org/pdf/2102.02779.pdfChoreoNet: Towards Music to Dance Synthesis with Choreographic Action Unit
Open
Paper
https://arxiv.org/pdf/2009.07637.pdf
Weakly-Supervised Deep Recurrent Neural
Networks for Basic Dance Step Generation
Open
Paper
step gen
https://arxiv.org/pdf/1807.01126.pdfCAN: Creative Adversarial Networks
Generating “Art” by Learning About Styles and
Deviating from Style Norms
Open
Paper
https://arxiv.org/pdf/1706.07068.pdf
Music-oriented Dance Video Synthesis with Pose Perceptual Loss
Open
Paper
https://arxiv.org/abs/1912.06606
GrooveNet: Real-Time Music-Driven Dance Movement
Generation using Artificial Neural Networks∗
Open
Paper
https://omid.al/docs/groovenet-ml4c-2017.pdf
ChoreoMaster: Choreography-Oriented Music-Driven Dance Synthesis
Open
Paper
자본의 향기가 가득한 논문, SIGGRAPH 2021
https://netease-gameai.github.io/ChoreoMaster/COUNT15
