Current diffusion-based video editing primarily focuses on
structure-preserved editing by utilizing various dense correspondences to
ensure temporal consistency and motion alignment. However, these approaches are
often ineffective when the target edit involves a shape change. To embark on
video editing with shape change, we explore customized video subject swapping
in this work, where we aim to replace the main subject in a source video with a
target subject having a distinct identity and potentially different shape. In
contrast to previous methods that rely on dense correspondences, we introduce
the VideoSwap framework that exploits semantic point correspondences, inspired
by our observation that only a small number of semantic points are necessary to
align the subject's motion trajectory and modify its shape. We also introduce
various user-point interactions (\eg, removing points and dragging points) to
address various semantic point correspondence. Extensive experiments
demonstrate state-of-the-art video subject swapping results across a variety of
real-world videos.

本文介绍了一种使用语义点对应的视频主体替换框架，通过选择性地使用少量语义点对应来对齐主体的运动轨迹和修改其形状，以实现视频编辑中的形状变化。在现实世界的多种视频中，我们进行了广泛的实验，展示了最先进的视频主体替换结果。

VideoSwap: 交互式语义点对应下的定制化视频主题替换

VideoSwap: Customized Video Subject Swapping with Interactive Semantic  Point Correspondence

Many organisms, including various species of spiders and caterpillars, change
their shape to switch gaits and adapt to different environments. Recent
technological advances, ranging from stretchable circuits to highly deformable
soft robots, have begun to make shape-changing robots a possibility. However,
it is currently unclear how and when shape change should occur, and what
capabilities could be gained, leading to a wide range of unsolved design and
control problems. To begin addressing these questions, here we simulate,
design, and build a soft robot that utilizes shape change to achieve locomotion
over both a flat and inclined surface. Modeling this robot in simulation, we
explore its capabilities in two environments and demonstrate the existence of
environment-specific shapes and gaits that successfully transfer to the
physical hardware. We found that the shape-changing robot traverses these
environments better than an equivalent but non-morphing robot, in simulation
and reality.

本文研究软机器人的形状变形如何实现在平坦和倾斜表面上的运动，通过模拟、仿真和实物实验，我们探索了该机器人在不同环境中运动的表现和性能，并发现形状变形使机器人在模拟和实际环境中比不变形机器人更优秀。

通过形状变化适应环境的软机器人

A soft robot that adapts to environments through shape change

A robot's mechanical parts routinely wear out from normal functioning and can
be lost to injury. For autonomous robots operating in isolated or hostile
environments, repair from a human operator is often not possible. Thus, much
work has sought to automate damage recovery in robots. However, every case
reported in the literature to date has accepted the damaged mechanical
structure as fixed, and focused on learning new ways to control it. Here we
show for the first time a robot that automatically recovers from unexpected
damage by deforming its resting mechanical structure without changing its
control policy. We found that, especially in the case of "deep insult", such as
removal of all four of the robot's legs, the damaged machine evolves shape
changes that not only recover the original level of function (locomotion) as
before, but can in fact surpass the original level of performance (speed). This
suggests that shape change, instead of control readaptation, may be a better
method to recover function after damage in some cases.

研究了一种自动从机械受损中恢复功能的机器人，采用形态变化而非控制器重新适配来提高表现，尤其在受到 “严重伤害”（例如四条腿全部断裂）时表现得更好。