📚 Pretraining¶

🎞️ ECCV2026 · 2 paper notes

360Anything: Geometry-Free Lifting of Images and Videos to 360°: 360Anything proposes a geometry-free diffusion Transformer framework that treats perspective inputs and panoramic targets uniformly as token sequences. By concatenating these sequences, the model autonomously learns the geometric correspondences between them without requiring any camera metadata. It lifts arbitrary-view images/videos into gravity-aligned, seamless 360° panoramas, completely outperforming prior state-of-the-art methods that rely on ground-truth camera parameters in both image and video tasks.
GryphOne: Symbol-Aware Masked Diffusion for Structural Refinement in Offline Handwritten Mathematical Expression Recognition: GryphOne redefines handwritten mathematical expression recognition (HMER) from autoregressive sequence generation to an iterative symbol refinement process via discrete masked diffusion. It maintains syntactic consistency under local editing using Symbol-Aware Tokenization (SAT) and enhances refinement stability through Random-Mask Mutual Learning (RMML). This approach comprehensively outperforms re-implemented autoregressive baselines and commercial HMER systems on MathWriting, achieving a 5.51% CER and a 59.9% ExpRate.