💻We've released the code for our #CVPR2025 paper MAtCha! 🍵MAtCha reconstructs sharp, accurate and scalable meshes of both foreground AND background from just a few unposed images (eg 3 to 10 images)... ...While also working with dense-view datasets (hundreds of images)!
Kyoto University Computer Vision Lab
@kyotovision.bsky.social
Computer Vision Laboratory @ Kyoto University (Ko Nishino, Ken Sakurada, Ryo Kawahara) https://vision.ist.i.kyoto-u.ac.jp/
Multistable Shape from Shading Emerges from Patch Diffusion #NeurIPS2024 Spotlight X. Nicole Han, T. Zickler and K. Nishino (Harvard+Kyoto) Diffusion-based SFS lets you sample multistable shape perception! Nicole at poster on Th 12/12 11am East A-C 1308 vision.ist.i.kyoto-u.ac.jp/research/mss...
PBDyG: Position Based Dynamic Gaussians for Motion-Aware Clothed Human Avatars Shota Sasaki, Jane Wu, Ko Nishino Human avatar with movement- (not pose-)dependent clothing as 3D GS simulated with PBD attached to SMPL, all recovered from multiview video. vision.ist.i.kyoto-u.ac.jp/research/pbdyg/
HeatFormer: A Neural Optimizer for Multiview Human Mesh Recovery Yuto Matsubara and Ko Nishino (Kyoto University) Occlusion-aware, view-flexible multiview human shape and pose recovery as learned optimization. vision.ist.i.kyoto-u.ac.jp/research/hea...
Correspondences of the Third Kind: Camera Pose Estimation from Object Reflection (ECCV24 Oral) Correspondences in the reflections let us disambiguate camera poses. No need of overlapping background; camera pose and 3D just from the shiny object surface. vision.ist.i.kyoto-u.ac.jp/research/3rd...