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Achieving 74.419% accuracy, this ensemble approach shows that self-supervised learning can dramatically enhance micro-gesture recognition performance.
Forget fine-tuning every LLM: ReQueR trains a single, RL-powered query refiner that coaxes hidden reasoning abilities out of diverse, frozen models at inference time.
Smoke-GS lets you see through the haze, reconstructing 3D scenes from smoky images with surprising clarity by explicitly modeling view-dependent smoke appearance.
Reconstructing 3D scenes from images obscured by smoke and extreme darkness is now significantly more achievable, thanks to insights gleaned from the NTIRE 2026 challenge.
