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🎷Layered PSD Diffusion🎷
👉OmniPSD produces layered PSD files with transparent alpha channels, separating text, foreground elements, and background into clean RGBA layers that can be directly edited in tools. Online Demo💙
👉Review https://t.ly/YNRAC
👉Paper arxiv.org/pdf/2512.09247
👉Project showlab.github.io/OmniPSD/
👉Demo https://www.lovart.ai/it
👉OmniPSD produces layered PSD files with transparent alpha channels, separating text, foreground elements, and background into clean RGBA layers that can be directly edited in tools. Online Demo💙
👉Review https://t.ly/YNRAC
👉Paper arxiv.org/pdf/2512.09247
👉Project showlab.github.io/OmniPSD/
👉Demo https://www.lovart.ai/it
🔥9❤8👍2
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🧱Pixel Art Volumetric Rendering🧱
👉Voxify3D is a novel differentiable two-stage framework bridging 3D mesh optimization with 2D pixel art supervision. Repo announced💙
👉Review https://t.ly/qPyNl
👉Paper https://lnkd.in/du5ikJGN
👉Project https://lnkd.in/dpiAjj5m
👉Repo TBA
👉Voxify3D is a novel differentiable two-stage framework bridging 3D mesh optimization with 2D pixel art supervision. Repo announced💙
👉Review https://t.ly/qPyNl
👉Paper https://lnkd.in/du5ikJGN
👉Project https://lnkd.in/dpiAjj5m
👉Repo TBA
❤7🔥4
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🫎 MoCapAnything is out 🫎
👉MoCapAnything is novel a reference-guided, factorized framework that first predicts 3D joint trajectories and then recovers asset-specific rotations via constraint-aware IK fitting. No code announced 🥲
👉Review https://t.ly/_Tw6t
👉Paper arxiv.org/pdf/2512.10881
👉Project animotionlab.github.io/MoCapAnything
👉MoCapAnything is novel a reference-guided, factorized framework that first predicts 3D joint trajectories and then recovers asset-specific rotations via constraint-aware IK fitting. No code announced 🥲
👉Review https://t.ly/_Tw6t
👉Paper arxiv.org/pdf/2512.10881
👉Project animotionlab.github.io/MoCapAnything
❤11👍4🔥4👏1🤯1😢1
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💚 MatAnyone 2 is out! 💚
👉MatAnyone 2 is the most advanced human video matting framework that preserves fine details by avoiding segmentation-like boundaries, while also shows enhanced robustness under challenging real-world conditions. Repo & Dataset announced💙
👉Review https://t.ly/vxOBO
👉Paper arxiv.org/pdf/2512.11782
👉Project pq-yang.github.io/projects/MatAnyone2
👉Repo github.com/pq-yang/MatAnyone2
👉MatAnyone 2 is the most advanced human video matting framework that preserves fine details by avoiding segmentation-like boundaries, while also shows enhanced robustness under challenging real-world conditions. Repo & Dataset announced💙
👉Review https://t.ly/vxOBO
👉Paper arxiv.org/pdf/2512.11782
👉Project pq-yang.github.io/projects/MatAnyone2
👉Repo github.com/pq-yang/MatAnyone2
🔥5❤4👍1👏1
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💷 SOTA Zero-Shot Stereo Matching💷
👉Fast-FoundationStereo by #Nvidia is a novel family of architectures that achieve, for the first time, strong zero-shot generalization at real-time frame rate via divide-&-conquer acceleration. Code & Data announced💙
👉Review https://t.ly/XD6pO
👉Paper https://lnkd.in/d9_YKW2A
👉Project https://lnkd.in/dKDxm7EX
👉Repo https://lnkd.in/dR4-PdsW
👉Fast-FoundationStereo by #Nvidia is a novel family of architectures that achieve, for the first time, strong zero-shot generalization at real-time frame rate via divide-&-conquer acceleration. Code & Data announced💙
👉Review https://t.ly/XD6pO
👉Paper https://lnkd.in/d9_YKW2A
👉Project https://lnkd.in/dKDxm7EX
👉Repo https://lnkd.in/dR4-PdsW
2🔥11❤4
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👀DriverGaze360: Driver SOTA👀
👉DriverGaze360 is a large-scale 360◦ field of view driver attention dataset, containing ∼1M gaze-labeled frames. Code & Dataset announced💙
👉Review https://t.ly/ZcoUw
👉Paper arxiv.org/pdf/2512.14266
👉Project av.dfki.de/drivergaze360/
👉Repo github.com/dfki-av/drivergaze360
👉Data av.dfki.de/drivergaze360/dataset
👉DriverGaze360 is a large-scale 360◦ field of view driver attention dataset, containing ∼1M gaze-labeled frames. Code & Dataset announced💙
👉Review https://t.ly/ZcoUw
👉Paper arxiv.org/pdf/2512.14266
👉Project av.dfki.de/drivergaze360/
👉Repo github.com/dfki-av/drivergaze360
👉Data av.dfki.de/drivergaze360/dataset
🔥11❤4
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🫠FlexAvatar: 3D Heads🫠
👉TUM introduces FlexAvatar, a novel method for creating HQ and complete 3D head avatars from a single image. Code announced💙
👉Review https://t.ly/Rkdtd
👉Paper arxiv.org/pdf/2512.15599
👉Project tobias-kirschstein.github.io/flexavatar/
👉Repo TBA
👉TUM introduces FlexAvatar, a novel method for creating HQ and complete 3D head avatars from a single image. Code announced💙
👉Review https://t.ly/Rkdtd
👉Paper arxiv.org/pdf/2512.15599
👉Project tobias-kirschstein.github.io/flexavatar/
👉Repo TBA
🔥8❤3👍1👏1
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🏜️ Depth Any Panoramas 🏜️
👉DAP is the new SOTA foundation model for panoramic depth estimation with a large scale dataset. Data & Repo under MIT💙
👉Review https://t.ly/LaUmd
👉Paper arxiv.org/pdf/2512.16913
👉Project https://lnkd.in/dvqNV9jx
👉Repo https://lnkd.in/dmNzhb-7
👉Demo https://lnkd.in/dDwjMF3u
👉DAP is the new SOTA foundation model for panoramic depth estimation with a large scale dataset. Data & Repo under MIT💙
👉Review https://t.ly/LaUmd
👉Paper arxiv.org/pdf/2512.16913
👉Project https://lnkd.in/dvqNV9jx
👉Repo https://lnkd.in/dmNzhb-7
👉Demo https://lnkd.in/dDwjMF3u
🔥9❤5👍2👏1
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🎯Generative Refocusing is out🎯
👉Generative Refocusing is a two-step process that uses DeblurNet to recover all-in-focus images from various inputs and BokehNet for creating controllable bokeh (in semi-supervised mode). Repo under Apache2.0💙
👉Review https://t.ly/8t7PA
👉Paper arxiv.org/pdf/2512.16923
👉Project generative-refocusing.github.io/
👉Repo github.com/rayray9999/Genfocus
👉Demo huggingface.co/spaces/nycu-cplab/Genfocus-Demo
👉Generative Refocusing is a two-step process that uses DeblurNet to recover all-in-focus images from various inputs and BokehNet for creating controllable bokeh (in semi-supervised mode). Repo under Apache2.0💙
👉Review https://t.ly/8t7PA
👉Paper arxiv.org/pdf/2512.16923
👉Project generative-refocusing.github.io/
👉Repo github.com/rayray9999/Genfocus
👉Demo huggingface.co/spaces/nycu-cplab/Genfocus-Demo
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