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Revtrosity

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51,433 görüntüleme • 7 ay önce •via X (Twitter)

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Ask me for the lottery numbers and play the inverse
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The House of Representatives is bitterly divided. New data show that after decades of pulling apart, Democrats and Republicans now present almost exactly inverse images of each other. Read the analysis:
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Jim Cramer says Deutsche Bank is fine ... RIP ... 😢 Inverse Cramer 🔊 ht 🤠The Only Man Buying Silver🤠
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Spum This is like, the inverse of Jim Henson's Dinosaurs snapping back against the simpsons by basically saying they were right. Its funny how things change.
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“Everyone else: No way! Alycia Debnam-Carey : I kinda wanna 🙂 The cast of #ItsWhatsInside had mixed reactions when asked if they’d play the game from the movie.” — via Inverse
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Airdrop Alpha: Want to automatically farm the two biggest Airdrops of 2026 and make money on top? 1. Visit Semantic Layer 2. Choose an AI model to copy or inverse trade 3. AI will automatically farm Polymarket (and Base) Everything fully on-chain via x402
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inverse les rôles ma belle. c’est pas toi qui perd, c’est toi qu’on perd 🫦
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inverse les rôles ma belle. c’est pas toi qui perd, c’est toi qu’on perd 🫦

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Just released a MuJoCo implementation of end-effector control with differential inverse kinematics. It's blazing fast, super readable, has 0 external dependencies and best of all, it's just a few lines of code:
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Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering discuss: The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formation process. While recent large-scale diffusion models have shown strong generative and inpainting capabilities, we find that current models do not sufficiently "understand" the scene shown in a single picture to generate consistent lighting effects (shadows, bright reflections, etc.) while preserving the identity and details of the composited object. We propose using a personalized large diffusion model as guidance to a physically based inverse rendering process. Our method recovers scene lighting and tone-mapping parameters, allowing the photorealistic composition of arbitrary virtual objects in single frames or videos of indoor or outdoor scenes. Our physically based pipeline further enables automatic materials and tone-mapping refinement.
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