CoMoVi co-generates 3D human motions and 2D videos synchronously in a single diffusion denoising loop using 3D-to-2D projection and dual-branch diffusion with 3D-2D cross attentions.
Realisdance-dit: Sim- ple yet strong baseline towards controllable character anima- tion in the wild.CoRR, abs/2504.14977
7 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
fields
cs.CV 7roles
background 1polarities
background 1representative citing papers
A training-free 3D scene-adaptive human animation framework that controls human motion and camera trajectories via ground-adaptive retargeting and visibility-masked point-cloud fusion in a diffusion backbone.
EMOSH proposes an Expressive Human Model with disentangled parameters, coarse-to-fine motion injection, and spatially-aligned conditioning to generate high-fidelity expressive human videos without driving-subject shape leakage.
Introduces mesh tokenization to condition DiT-based video diffusion models directly on 3D human meshes for motion control without 2D rendering.
EverAnimate restores drifted latent flow trajectories in chunked video generation via persistent latent propagation and restorative flow matching, achieving measurable gains in PSNR, SSIM, LPIPS, and FID over prior long-animation methods with only LoRA tuning.
SteadyDancer is an I2V framework using condition reconciliation, synergistic pose modulation, and staged training to achieve robust first-frame preservation and coherent motion control in human image animation.
A decoupled-control autoregressive video model using Fast-Slow Memory training, dynamic projection, and staged camera control to produce stable long-horizon outputs with human and viewpoint guidance.
citing papers explorer
-
CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos
CoMoVi co-generates 3D human motions and 2D videos synchronously in a single diffusion denoising loop using 3D-to-2D projection and dual-branch diffusion with 3D-2D cross attentions.
-
3D Scene-Adaptive Trajectory-Controllable Human Image Animation with Camera Movement
A training-free 3D scene-adaptive human animation framework that controls human motion and camera trajectories via ground-adaptive retargeting and visibility-masked point-cloud fusion in a diffusion backbone.
-
EMOSH: Expressive Motion and Shape Disentanglement for Human Animation
EMOSH proposes an Expressive Human Model with disentangled parameters, coarse-to-fine motion injection, and spatially-aligned conditioning to generate high-fidelity expressive human videos without driving-subject shape leakage.
-
Towards 3D-Aware Video Diffusion Models: Render-Free Human Motion Control with Mesh Tokenization
Introduces mesh tokenization to condition DiT-based video diffusion models directly on 3D human meshes for motion control without 2D rendering.
-
EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration
EverAnimate restores drifted latent flow trajectories in chunked video generation via persistent latent propagation and restorative flow matching, achieving measurable gains in PSNR, SSIM, LPIPS, and FID over prior long-animation methods with only LoRA tuning.
-
SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation
SteadyDancer is an I2V framework using condition reconciliation, synergistic pose modulation, and staged training to achieve robust first-frame preservation and coherent motion control in human image animation.
-
Directing the World: Fast Autoregressive Video Generation with Compositional Human-Camera Control
A decoupled-control autoregressive video model using Fast-Slow Memory training, dynamic projection, and staged camera control to produce stable long-horizon outputs with human and viewpoint guidance.