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Learning to Generate Diverse Dance Motions with Transformer
[article]
2020
arXiv
pre-print
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We also present a novel two-stream motion transformer generative model, which can generate motion sequences with high flexibility. ...
We introduce a complete system for dance motion synthesis, which can generate complex and highly diverse dance sequences given an input music sequence. ...
In this work, we introduce a novel system that can synthesize diverse dance motions by learning from a large-scale dataset with a comprehensive set of highly diverse dance movements. ...
arXiv:2008.08171v1
fatcat:kp57scjce5cnlejdqpukvhurem
Transflower: probabilistic autoregressive dance generation with multimodal attention
[article]
2021
arXiv
pre-print
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attend over a large motion and music context are necessary to produce interesting, diverse, and realistic dance that matches the music. ...
Second, we introduce the currently largest 3D dance-motion dataset, obtained with a variety of motion-capture technologies, and including both professional and casual dancers. ...
Learning to Generate Diverse Dance Motions with Transformer. arXiv preprint
Heewoo Jun, Tom B Brown, Prafulla Dhariwal, Scott Gray, et al. 2020. ...
arXiv:2106.13871v1
fatcat:ofkengygabcfdlbcwsl6vk4rmq
AI Choreographer: Music Conditioned 3D Dance Generation with AIST++
[article]
2021
arXiv
pre-print
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We present AIST++, a new multi-modal dataset of 3D dance motion and music, along with FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion conditioned on music. ...
We show that naively applying sequence models such as transformers to this dataset for the task of music conditioned 3D motion generation does not produce satisfactory 3D motion that is well correlated ...
Generation Diversity We also evaluate our model's ability to generate diverse dance motions when given various input music compared with the baseline methods. ...
arXiv:2101.08779v3
fatcat:gsdbkgtq7vb7xhxsfrmfb43tke
Bailando: 3D Dance Generation by Actor-Critic GPT with Choreographic Memory
[article]
2022
arXiv
pre-print
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To achieve synchronized alignment between diverse motion tempos and music beats, we introduce an actor-critic-based reinforcement learning scheme to the GPT with a newly-designed beat-align reward function ...
sequence to a quantized codebook, 2) an actor-critic Generative Pre-trained Transformer (GPT) that composes these units to a fluent dance coherent to the music. ...
This research is conducted in collaboration with SenseTime. This work is supported by NTU NAP and A*STAR through the Industry Alignment Fund -Industry Collaboration Projects Grant. ...
arXiv:2203.13055v2
fatcat:rw5ixqeyynevdcsdkcjs7stfka
Dance Generation with Style Embedding: Learning and Transferring Latent Representations of Dance Styles
[article]
2021
arXiv
pre-print
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Choreography refers to creation of dance steps and motions for dances according to the latent knowledge in human mind, where the created dance motions are in general style-specific and consistent. ...
So far, such latent style-specific knowledge about dance styles cannot be represented explicitly in human language and has not yet been learned in previous works on music-to-dance generation tasks. ...
As descripted in Figure 2 , we apply a set of transformer music encoders with a Bi-LSTM dance generator in music-to-dance generator. ...
arXiv:2104.14802v1
fatcat:jkecjargvrc2naypu4huynngra
DanceConv: Dance Motion Generation with Convolutional Networks
2022
IEEE Access
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Subjective results confirm the effectiveness of our approach to synthesize diverse dance motion sequences, reporting a 6% increase in style consistency preference according to 1800 answers provided by ...
Based on this outcome, we train the proposed multimodal architecture with two different approaches, namely teacher-forcing and self-supervised curriculum learning, to deal with the autoregressive error ...
They also would like to thank all the colleagues and friends that participated in both user-studies and provided their valuable feedback. ...
doi:10.1109/access.2022.3169782
fatcat:abjqqrrww5bulh5tadggkwzk4u
DanceFormer: Music Conditioned 3D Dance Generation with Parametric Motion Transformer
[article]
2021
arXiv
pre-print
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In this paper, we reformulate it by a two-stage process, ie, a key pose generation and then an in-between parametric motion curve prediction, where the key poses are easier to be synchronized with the ...
Previous works treat this task as sequence generation, however, it is challenging to render a music-aligned long-term sequence with high kinematic complexity and coherent movements. ...
The generation diversity is ensured by the adversarial learning scheme. ...
arXiv:2103.10206v4
fatcat:tqsqxlrhffaxxaujfsgake5zwm
Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning
[article]
2021
arXiv
pre-print
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In this paper, we formalize the music-conditioned dance generation as a sequence-to-sequence learning problem and devise a novel seq2seq architecture to efficiently process long sequences of music features ...
Furthermore, we propose a novel curriculum learning strategy to alleviate error accumulation of autoregressive models in long motion sequence generation, which gently changes the training process from ...
generation with music. (2) We propose a novel curriculum learning strategy to alleviate error accumulation of autoregressive models in long motion sequence generation. (3) To facilitate long-term dance ...
arXiv:2006.06119v7
fatcat:gmii276zgjdkxcisfsp4sb5ubm
Dual Learning Music Composition and Dance Choreography
[article]
2022
arXiv
pre-print
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2021
Proceedings of the 29th ACM International Conference on Multimedia
unpublished
doi:10.1145/3474085.3475180 fatcat:ogt6rmevwbhvtg3lo3r26mvgiu
doi:10.1145/3474085.3475180 fatcat:ogt6rmevwbhvtg3lo3r26mvgiu
Experimental results demonstrate that our dual learning framework improves individual task performance, delivering generated music compositions and dance choreographs that are realistic and faithful to ...
Recent research works have studied generative models for dance sequences conditioned on music. The dual task of composing music for given dances, however, has been largely overlooked. ...
With the advent of deep learning methods, sequence-to-sequence models have been proposed for generating dance sequences from encoded music features. ...
arXiv:2201.11999v1
fatcat:ktgq7skannbkdiajjlm7rerb4y
Music-to-Dance Generation with Optimal Transport
[article]
2022
arXiv
pre-print
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In this paper, we propose a Music-to-Dance with Optimal Transport Network (MDOT-Net) for learning to generate 3D dance choreographies from music. ...
It has been tackled by different approaches such as similarity retrieval, sequence-to-sequence modeling and generative adversarial networks, but their generated dance sequences are often short of motion ...
Another shortcoming is the inability to generate diverse dance sequences. [ Huang et al., 2021] proposes curriculum learning with L1 loss on the dance sequences to alleviate the motion freezing issue ...
arXiv:2112.01806v2
fatcat:dwguh76gmffhdj4fjfo4yz5stu
Hierarchical Style-based Networks for Motion Synthesis
[article]
2020
arXiv
pre-print
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Our proposed method learns to model the motion of human by decomposing a long-range generation task in a hierarchical manner. ...
We first propose to explicitly disentangle the provided motion material into style and content counterparts via bi-linear transformation modelling, where diverse synthesis is achieved by free-form combination ...
It is capable of generating motion with different styles (e.g., motion of novice ballet or modern dance of an expert) by optimizing with a cross-entropy framework. ...
arXiv:2008.10162v1
fatcat:yd4zkg64vzeqbf4xop7nzbfxv4
Music2Dance: DanceNet for Music-driven Dance Generation
[article]
2020
arXiv
pre-print
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In this paper, we propose a novel autoregressive generative model, DanceNet, to take the style, rhythm and melody of music as the control signals to generate 3D dance motions with high realism and diversity ...
It is challenging due to not only the requirement of realistic and complex human motions for dance, but more importantly, the synthesized motions should be consistent with the style, rhythm and melody ...
Our goal is to generate realistic, diverse and music-consistent dance motion. ...
arXiv:2002.03761v2
fatcat:rkxfottbbrbutneemt4mwmedya
Towards 3D Dance Motion Synthesis and Control
[article]
2020
arXiv
pre-print
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In this paper, we propose a novel generative motion model based on temporal convolution and LSTM,TC-LSTM, to synthesize realistic and diverse dance motion. ...
Unlike regular simple locomotion, it is challenging to synthesize artistic dance motions due to the irregularity, kinematic complexity and diversity. ...
frames(30 frames), our model can generate realistic and diverse dance sequences with its own style. ...
arXiv:2006.05743v1
fatcat:nb2inkafqjfzlehap346q2zb7m
Dancing with cultural difference: Challenges, transformation and reflexivity in culturally pluralist dance education
2013
Dance Research Aotearoa
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Transformative learning and developing a reflexive view of dances from different cultures are pedagogical concepts that underpin the ANZC and I position them as key to exploring some transformations that ...
My main aim in this article is to inform and support the development of an ethical and sustainable culturally pluralist pedagogy in which our responsibilities to the people whose dances we study are an ...
different, and one would hope, transformational understandings of what dance 'is' for diverse people and cultures; • inform teachers as to how to integrate theory with dancing, thus avoiding a theory/practice ...
doi:10.15663/dra.v1i1.3
fatcat:5neqdubbczcojo2pz5c446gobm
Flow Guided Transformable Bottleneck Networks for Motion Retargeting
[article]
2021
arXiv
pre-print
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Armed with both 3D object understanding and end-to-end learned rendering, this categorically novel representation delivers state-of-the-art image generation quality, as shown by our quantitative and qualitative ...
Human motion retargeting aims to transfer the motion of one person in a "driving" video or set of images to another person. ...
Our method can generate realistic images from diverse motion patterns. Youtube-Dancing dataset. ...
arXiv:2106.07771v1
fatcat:yjprgqyphbdenkfxguq5dpysxu
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