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Jia-Bin Huang

@jbhuang0604 • 77,845 subscribers

I am the one who wears a jacket.

Shorts

Text-to-image generators are incredible! But why must we use *plain text* as the interface? 🤔 Check out Rich Text-to-Image generation! Rich Text offers an intuitive and expressive way to explore your visual imagination. Some of my favorite examples. 👇

Text-to-image generators are incredible! But why must we use plain text as the interface? 🤔 Check out Rich Text-to-Image generation! Rich Text offers an intuitive and expressive way to explore your visual imagination. Some of my favorite examples. 👇

73,372 次观看

How can we reconstruct 3D objects under *extreme lighting variations*? 🌤️🌥️🌆🌃🌉 How about ... 🤔 appearance embedding? BUT it cannot capture view-dependent appearances. 🤔 inverse rendering? BUT it suffers from ambiguities. 💡 Our idea: Relighting comes to the rescue!

How can we reconstruct 3D objects under extreme lighting variations? 🌤️🌥️🌆🌃🌉 How about ... 🤔 appearance embedding? BUT it cannot capture view-dependent appearances. 🤔 inverse rendering? BUT it suffers from ambiguities. 💡 Our idea: Relighting comes to the rescue!

33,092 次观看

Beyond photos/videos, what's the next medium for sharing visual experiences? 🤔 NeRF/3DGS are great but only capture a static 3D world and ignore ambient scene dynamics. In this paper, we show how we can reconstruct/render these essential scene elements even with a single causal video.

Beyond photos/videos, what's the next medium for sharing visual experiences? 🤔 NeRF/3DGS are great but only capture a static 3D world and ignore ambient scene dynamics. In this paper, we show how we can reconstruct/render these essential scene elements even with a single causal video.

28,722 次观看

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Explaining Flow Matching in 4 minutes

Explaining Flow Matching in 4 minutes

59,938 次观看 • 10 个月前

Introducing Generative Omnimatte: A method for decomposing a video into complete layers, including objects and their associated effects (e.g., shadows, reflections). It enables many cool applications, such as video stylization, compositions, moment retiming, and object removal.

Introducing Generative Omnimatte: A method for decomposing a video into complete layers, including objects and their associated effects (e.g., shadows, reflections). It enables many cool applications, such as video stylization, compositions, moment retiming, and object removal.

81,713 次观看 • 1 年前

Exploration is key for robots to generalize, especially in open-ended environments with vague goals and sparse rewards. BUT, how do we go beyond random poking? Wouldn't it be great to have a robot that explores an environment just like a kid? Introducing Imagine, Verify, Execute (IVE)! IVE leverages Vision-Language models to • extract semantic scene graphs, • imagine novel scenes, • predict their physical plausibility, and • generate executable sequences. IVE is a memory-guided agentic exploration framework that operates fully automatically, enabling more diverse and meaningful exploration.

Exploration is key for robots to generalize, especially in open-ended environments with vague goals and sparse rewards. BUT, how do we go beyond random poking? Wouldn't it be great to have a robot that explores an environment just like a kid? Introducing Imagine, Verify, Execute (IVE)! IVE leverages Vision-Language models to • extract semantic scene graphs, • imagine novel scenes, • predict their physical plausibility, and • generate executable sequences. IVE is a memory-guided agentic exploration framework that operates fully automatically, enabling more diverse and meaningful exploration.

45,285 次观看 • 1 年前

3D Gaussian Splatting is awesome! BUT, the 3D Gaussian primitives often have difficulty reconstructing fine appearance details. 😩 Meet Textured Gaussians! ✋ Our RGBA Textured Gaussians enhance 3D scene appearance modeling. Small change, BIG improvement!

3D Gaussian Splatting is awesome! BUT, the 3D Gaussian primitives often have difficulty reconstructing fine appearance details. 😩 Meet Textured Gaussians! ✋ Our RGBA Textured Gaussians enhance 3D scene appearance modeling. Small change, BIG improvement!

39,657 次观看 • 1 年前

Some papers rejected due to "incremental novelty" 🫠 We as a community should emphasize less on being novel and more on being simple, interesting, and useful.

Some papers rejected due to "incremental novelty" 🫠 We as a community should emphasize less on being novel and more on being simple, interesting, and useful.

32,114 次观看 • 1 年前

3D illusions are fascinating! 🤩 But it takes exceptional artistic skills to make one. We present Illusion3D - a simple method for creating 3D multiview illusions, where the interpretations change depending on your perspectives. Let's play Where's Waldo, shall we? 😆

3D illusions are fascinating! 🤩 But it takes exceptional artistic skills to make one. We present Illusion3D - a simple method for creating 3D multiview illusions, where the interpretations change depending on your perspectives. Let's play Where's Waldo, shall we? 😆

34,483 次观看 • 1 年前

Can we enable free-viewpoint renderings of scenes under various lighting conditions? Yes, we can! And just from SINGLE videos. Here are 🌃 night simulations from input videos with hard shadows.

Can we enable free-viewpoint renderings of scenes under various lighting conditions? Yes, we can! And just from SINGLE videos. Here are 🌃 night simulations from input videos with hard shadows.

26,281 次观看 • 1 年前

Capturing out-of-focus photos is sooo frustrating! 😩 Check out our work on defocus control with dual-camera 📸 #CVPR2023 Our method can refocus and adjust the depth of field AFTER you capture the photograph! 🤩 Paper: Project:

Capturing out-of-focus photos is sooo frustrating! 😩 Check out our work on defocus control with dual-camera 📸 #CVPR2023 Our method can refocus and adjust the depth of field AFTER you capture the photograph! 🤩 Paper: Project:

41,330 次观看 • 3 年前

New Video! Excited to share our work on fast view synthesis of casual videos. 🤩 high-quality dynamic view synthesis 🤩 applicable for a wide range of casual videos 🤩 fast training and rendering

New Video! Excited to share our work on fast view synthesis of casual videos. 🤩 high-quality dynamic view synthesis 🤩 applicable for a wide range of casual videos 🤩 fast training and rendering

27,359 次观看 • 2 年前

How do we go beyond reconstructing colors and recovering the intrinsic scene properties? 🤔 👁️ IRIS: Inverse Rendering of Indoor Scenes IRIS estimates accurate material, lighting, and camera response functions given a set of LDR images, enabling photorealistic and view-consistent relighting and object insertion.

How do we go beyond reconstructing colors and recovering the intrinsic scene properties? 🤔 👁️ IRIS: Inverse Rendering of Indoor Scenes IRIS estimates accurate material, lighting, and camera response functions given a set of LDR images, enabling photorealistic and view-consistent relighting and object insertion.

15,917 次观看 • 1 年前

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