ReImagine decouples human appearance from temporal consistency via pretrained image backbones, SMPL-X motion guidance, and training-free video diffusion refinement to generate high-quality controllable videos.
arXiv preprint arXiv:2505.01838 (2025) 3, 10
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HiReFF presents a feed-forward framework for 2K human video reconstruction from uncalibrated sparse-view videos via scale-synchronized calibration, Gaussian masking, and high-resolution side-tuning.
VolHuMe is a new high-resolution volumetric human mesh dataset with 104 subjects, multi-view imagery, SMPL-X fits, rigged meshes, garment labels, and detailed hand/face geometry, benchmarked on reconstruction tasks.
citing papers explorer
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ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis
ReImagine decouples human appearance from temporal consistency via pretrained image backbones, SMPL-X motion guidance, and training-free video diffusion refinement to generate high-quality controllable videos.
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HiReFF: High-Resolution Feedforward Human Reconstruction from Uncalibrated Sparse-View Video
HiReFF presents a feed-forward framework for 2K human video reconstruction from uncalibrated sparse-view videos via scale-synchronized calibration, Gaussian masking, and high-resolution side-tuning.
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VolHuMe: a High-Resolution Large Scale Dataset of Volumetric Human Meshes
VolHuMe is a new high-resolution volumetric human mesh dataset with 104 subjects, multi-view imagery, SMPL-X fits, rigged meshes, garment labels, and detailed hand/face geometry, benchmarked on reconstruction tasks.