R2VD redefines reconstruction as the origin for residual-guided vector diffusion across PPE, GMP, RSM, and VDI stages to achieve superior anomaly detectability and background suppression on eight datasets.
Scalable diffusion models with transformers
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LiftFormer transforms monocular depth prediction into depth-oriented geometric and edge-aware subspace representations via lifting and frame theory, achieving state-of-the-art results on standard datasets.
A three-stage plug-and-play framework uses proxy HSIs, blur-robust diffusion synthesis, and spectral transfer to augment training data for target-adaptive hyperspectral restoration.
Open-Sora releases an open-source video generation model based on a Spatial-Temporal Diffusion Transformer that decouples spatial and temporal attention, supporting text-to-video, image-to-video, and text-to-image tasks with claimed high fidelity.
DCGNet combines dynamic multi-granularity detection, underwater physics priors for degradation restoration, spatial Gaussian saliency, and a diffusion transformer to outperform prior methods on underwater SOD benchmarks.
citing papers explorer
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Beyond Reconstruction: Reconstruction-to-Vector Diffusion for Hyperspectral Anomaly Detection
R2VD redefines reconstruction as the origin for residual-guided vector diffusion across PPE, GMP, RSM, and VDI stages to achieve superior anomaly detectability and background suppression on eight datasets.
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LiftFormer: Lifting and Frame Theory Based Monocular Depth Estimation Using Depth and Edge Oriented Subspace Representation
LiftFormer transforms monocular depth prediction into depth-oriented geometric and edge-aware subspace representations via lifting and frame theory, achieving state-of-the-art results on standard datasets.
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HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation
A three-stage plug-and-play framework uses proxy HSIs, blur-robust diffusion synthesis, and spectral transfer to augment training data for target-adaptive hyperspectral restoration.
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Open-Sora: Democratizing Efficient Video Production for All
Open-Sora releases an open-source video generation model based on a Spatial-Temporal Diffusion Transformer that decouples spatial and temporal attention, supporting text-to-video, image-to-video, and text-to-image tasks with claimed high fidelity.
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Rethinking Conditional Generation for Underwater Salient Object Detection
DCGNet combines dynamic multi-granularity detection, underwater physics priors for degradation restoration, spatial Gaussian saliency, and a diffusion transformer to outperform prior methods on underwater SOD benchmarks.