Creating group choreography from music has gained attention in cultural
entertainment and virtual reality, aiming to coordinate visually cohesive and
diverse group movements. Despite increasing interest, recent works face
challenges in achieving aesthetically appealing choreography, primarily for two
key issues: multi-dancer collision and single-dancer foot slide. To address
these issues, we propose a Trajectory-Controllable Diffusion (TCDiff), a novel
approach that harnesses non-overlapping trajectories to facilitate coherent
dance movements. Specifically, to tackle dancer collisions, we introduce a
Dance-Beat Navigator capable of generating trajectories for multiple dancers
based on the music, complemented by a Distance-Consistency loss to maintain
appropriate spacing among trajectories within a reasonable threshold. To
mitigate foot sliding, we present a Footwork Adaptor that utilizes trajectory
displacement from adjacent frames to enable flexible footwork, coupled with a
Relative Forward-Kinematic loss to adjust the positioning of individual
dancers' root nodes and joints. Extensive experiments demonstrate that our
method achieves state-of-the-art results.

使用非重叠轨迹来协助协调舞蹈运动，并通过距离保持一定阈值和相对前向运动的损失来解决多舞者碰撞和单人滑步问题，实现了最先进的结果。

具有轨迹可控扩散的和谐团体编排

Harmonious Group Choreography with Trajectory-Controllable Diffusion

Music-driven group choreography poses a considerable challenge but holds
significant potential for a wide range of industrial applications. The ability
to generate synchronized and visually appealing group dance motions that are
aligned with music opens up opportunities in many fields such as entertainment,
advertising, and virtual performances. However, most of the recent works are
not able to generate high-fidelity long-term motions, or fail to enable
controllable experience. In this work, we aim to address the demand for
high-quality and customizable group dance generation by effectively governing
the consistency and diversity of group choreographies. In particular, we
utilize a diffusion-based generative approach to enable the synthesis of
flexible number of dancers and long-term group dances, while ensuring coherence
to the input music. Ultimately, we introduce a Group Contrastive Diffusion
(GCD) strategy to enhance the connection between dancers and their group,
presenting the ability to control the consistency or diversity level of the
synthesized group animation via the classifier-guidance sampling technique.
Through intensive experiments and evaluation, we demonstrate the effectiveness
of our approach in producing visually captivating and consistent group dance
motions. The experimental results show the capability of our method to achieve
the desired levels of consistency and diversity, while maintaining the overall
quality of the generated group choreography.

利用扩散式生成方法和群舞动画控制策略生成高质量、可定制的群舞，以满足多样性和一致性需求，实验证明了方法的有效性。