CVPR 2026採択の論文「Beyond Single Object: Learning 3D Relations with Large Language Models」( https://t.co/Mkh9PmNbq4 )について、産総研からプレスリリース( https://t.co/iBVZfyAnqJ )が。点群言語モデルのコードとデータセット( https://t.co/XDcZcfAFO8 )も公開されています。
#CVPR2026 / @CVPR
We've released the CVPR 2026 Report!
https://t.co/eddjqETFSk
Compiled during CVPR through a collaboration among LIMIT.Lab, cvpaper.challenge, and the Visual Geometry Group (VGG), this report provides meta-level insights into the key trends, research directions, emerging themes, and discussions that shaped this year's conference.
📢 [CVPR’26] Can we learn to detect, segment, and track every object in a video without human supervision?
Yes, we introduce VideoCUPS, the first unsupervised video panoptic segmentation (VPS) method: 1. Get pseudo-labels from monocular videos. 2. Train a VPS model on them.