Bing Xu
@_bingxu
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Computer graphics/light transport/rendering. Painting. PhD @UCSanDiego. Art at https://t.co/dRpuV5I7UM
San Diego, CA
Joined October 2013
🌲Introducing our paper A generalizable light transport 3D embedding for Global Illumination https://t.co/qW04w1NdLU. Just as Transformers learn long-range relationships between words or pixels, our new paper shows they can also learn how light interacts and bounces around a 3D
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Guard the tools to create high quality 3D. Otherwise we’ll end up in a recursive loop of low-quality input, low-quality output. Time for monthly donate
Last year, Autodesk made $315 million from mostly 3ds Max and Maya subscriptions. Over the same period, Blender made €3.1M, or 1% of Autodesk's earnings, despite having significantly more users. This is the wrong way around. Be someone that supports the next generation of
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Did Blender help you this year? Help back! If every active user contributed $5 this month, Blender would be funded for the entire year 2026. Professional 3D software. No subscriptions. No limits. Just your support. Do your part. Donate today. https://t.co/YJFi7Fc6FQ
#b3d
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Announcing: New @Steam Hardware, coming in 2026: Steam Controller Steam Machine Steam Frame Watch our jazzy announcement video and wishlist now: https://t.co/TUKoZdzn9B
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By the way, we spent a lot of effort curating and will release a large-scale indoor dataset (∼14k scenes) with diverse floorplans, geometries, and textures, serving as a benchmark for learning light transport. Checkout the paper for further details! https://t.co/qW04w1NdLU
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We demonstrate the versatility of our framework by reusing a shared pre-trained encoder while introducing task-specific decoders. Using the same model, we accurately estimate diffuse global illumination that generalizes across diverse indoor scenes. With limited fine-tuning on a
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Paul Graham on why startups should deliberately choose hard problems:
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HDRView 2.5 is available! Lots of new features, including support for DDS textures and animated GIF/JXL/PNG files, a new animation/playback mode, new blackpoint/offset option when tone mapping, and many UI improvements. https://t.co/9HDyUb6FXp.
#HDR, #HDRI, #dearimgui
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New Black Myth title—officially unveiled today! No ghosts walked the earth till born of human heart; Onstage and off, immortals fall to fiends—their perfected art. Indoors and out, the judge is bound by the same household ties; The sun is veiled, the moon unmoved—who decrees who
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🥻Our new #SIGGRAPH2025 paper introduces a novel pipeline that captures and digitizes physical threads, predicts fabric appearance from the weaving pattern, and aids designers in exploring new possibilities. 🔗 https://t.co/yxGj3mHuY3
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#ICCV2025 Introducing💡LightSwitch💡- A multi-view material-relighting diffusion pipeline that directly and efficiently relights any number of input images to a target lighting & do 3D asset relighting with gaussian splatting! 🧵
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Listen to Alan Wake.
Check out our paper "Appearance-Preserving Scene Aggregation for Level-of-Detail Rendering" at #SIGGRAPH2025 Thu 08/10 at 2:50pm in the "Neural Materials & LOD" session. Project page: https://t.co/kh7TDLfVFx. (To those who watched fast forward: did I blow your mind?🤣)
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More on this topic. 😋
🎮⚽ Do you like football or football games? ⚽🎮 🎉 I’m excited to share that our paper has been accepted to ACM SIGGRAPH 2025, journal track! 🎉 🔹 PhysicsFC: Learning User-Controlled Skills for a Physics-Based Football Player Controller. Minsu Kim, Eunho Jung, Yoonsang Lee*
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Seven graphics things (well, more) for today, including the new book GPU Zen 3 (w00t!) and Doom run using E. coli cells. https://t.co/GGvo6Wytxz
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Mental map of Markov Chain Monte Carlo (MCMC) algorithms, and analogous machine learning (ML) algorithms [dashed = especially loose analogy]. Grey boxes are basic tools, and each arrow is annotated with the "delta" between algorithms.
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https://t.co/F1d85YqWGz Check out Wesley, Xuanda, and Yash's latest work on combining cross bilateral filtering and Adam to make optimization in graphics more robust and fast, through better preconditioning the gradient.
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https://t.co/svi8ps7js7 Rendering nerds! Check out Ziyang Fu's latest work, where he shows that low-dimensional, deterministic diffusion models can be useful for importance sampling in Monte Carlo rendering applications.
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