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Only Research#Image generation
October 29Thursday
  1. inclusionAI Repositories52

    Inclusion AI's IDM matches generator EMA features to speed up one-step and two-step text-to-image generation

    Inclusion AI and academic collaborators released IDM, a distillation method that combines internal distribution matching with moment matching in the generator's own EMA feature space, removing the need for an external feature encoder. At 2 NFE, IDM (Z-Image) scores 94.25% on LongText-CN and 90.20% on LongText-EN, and full-parameter IDM (Z-Image) runs in 0.25 s at 1 NFE and 0.30 s at 2 NFE on a single A100 in BF16. The same trained checkpoint supports both 1-NFE and 2-NFE sampling, and the code is released under Apache 2.0, while the checkpoints are listed as coming soon.

October 26Monday
  1. Apple Machine Learning Research34

    GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior

    Apple researchers present GHARP, a method that animates 3D human heads in real time from a few input images plus a driving expression signal, splitting the task into an offline identity stage and a lightweight runtime animation stage. A body alignment network removes ambiguity from body pose and clothing, and GHARP reaches state-of-the-art quality on the Ava-256 benchmark while running up to 13× faster on an A100 GPU with 8× fewer Gaussians.

October 21Wednesday
  1. Apple Machine Learning Research26

    TEAL: Token-Space Efficient Active Learning for Low-Budget Semantic Segmentation

    Apple researchers (with University of Waterloo) introduce TEAL, the first pixel-level active learning framework built on frozen ViT representations, selecting diverse candidates directly on the native token lattice via a two-level MaxHerding strategy plus margin-based uncertainty refinement. With a single labeled pixel per image, TEAL beats the strongest baseline by up to +24.36 mIoU on CamVid, Cityscapes, ADE20K and Pascal Context, reaching up to 97% of fully supervised performance with just 10 px.