BREAKING NEWS
LATEST POSTS
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Odyssey.systems Explorer – pioneering generative world models and gaussian splatting
Odyssey and a Pixar co-founder, Ed Catmull (also an investor), just dropped Explorer, a revolutionary 3D world generator that turns any image into an editable 3D world.
https://odyssey.systems/introducing-explorer
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Genesis AI – a physics platform designed for general purpose Robotics/Embodied AI/Physical AI applications
https://github.com/Genesis-Embodied-AI/Genesis
https://genesis-world.readthedocs.io/en/latest
Genesis is a physics platform designed for general purpose Robotics/Embodied AI/Physical AI applications. It is simultaneously multiple things:
- A universal physics engine re-built from the ground up, capable of simulating a wide range of materials and physical phenomena.
- A lightweight, ultra-fast, pythonic, and user-friendly robotics simulation platform.
- A powerful and fast photo-realistic rendering system.
- A generative data engine that transforms user-prompted natural language description into various modalities of data.
FEATURED POSTS
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SwarmUI.net – A free, open source, modular AI image generation Web-User-Interface
https://github.com/mcmonkeyprojects/SwarmUI
A Modular AI Image Generation Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility. Supports AI image models (Stable Diffusion, Flux, etc.), and AI video models (LTX-V, Hunyuan Video, Cosmos, Wan, etc.), with plans to support eg audio and more in the future.
SwarmUI by default runs entirely locally on your own computer. It does not collect any data from you.
SwarmUI is 100% Free-and-Open-Source software, under the MIT License. You can do whatever you want with it.
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WhatDreamsCost Spline-Path-Control – Create motion controls for ComfyUI
https://github.com/WhatDreamsCost/Spline-Path-Control
https://whatdreamscost.github.io/Spline-Path-Control/
https://github.com/WhatDreamsCost/Spline-Path-Control/tree/main/example_workflows
Spline Path Control is a simple tool designed to make it easy to create motion controls. It allows you to create and animate shapes that follow splines, and then export the result as a
.webm
video file.
This project was created to simplify the process of generating control videos for tools like VACE. Use it to control the motion of anything (camera movement, objects, humans etc) all without extra prompting.- Multi-Spline Editing: Create multiple, independent spline paths
- Easy To Use Controls: Quickly edit splines and points
- Full Control of Splines and Shapes:
- Start Frame: Set a delay before a spline’s animation begins.
- Duration: Control the speed of the shape along its path.
- Easing: Apply
Linear
,Ease-in
,Ease-out
, andEase-in-out
functions for smooth acceleration and deceleration. - Tension: Adjust the “curviness” of the spline path.
- Shape Customization: Change the shape (circle, square, triangle), size, fill color, and border.
- Reference Images: Drag and drop or upload a background image to trace paths over an existing image.
- WebM Export: Export your animation with a white background, perfect for use as a control video in VACE.
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AI Data Laundering: How Academic and Nonprofit Researchers Shield Tech Companies from Accountability
“Simon Willison created a Datasette browser to explore WebVid-10M, one of the two datasets used to train the video generation model, and quickly learned that all 10.7 million video clips were scraped from Shutterstock, watermarks and all.”
“In addition to the Shutterstock clips, Meta also used 10 million video clips from this 100M video dataset from Microsoft Research Asia. It’s not mentioned on their GitHub, but if you dig into the paper, you learn that every clip came from over 3 million YouTube videos.”
“It’s become standard practice for technology companies working with AI to commercially use datasets and models collected and trained by non-commercial research entities like universities or non-profits.”
“Like with the artists, photographers, and other creators found in the 2.3 billion images that trained Stable Diffusion, I can’t help but wonder how the creators of those 3 million YouTube videos feel about Meta using their work to train their new model.”
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Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipeline
https://jo.dreggn.org/home/2018_manuka.pdf
http://www.fxguide.com/featured/manuka-weta-digitals-new-renderer/
The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture. In its core, reyes is based on stochastic rasterisation of micropolygons, facilitating depth of field, motion blur, high geometric complexity,and programmable shading.
This is commonly achieved with Monte Carlo path tracing, using a paradigm often called shade-on-hit, in which the renderer alternates tracing rays with running shaders on the various ray hits. The shaders take the role of generating the inputs of the local material structure which is then used bypath sampling logic to evaluate contributions and to inform what further rays to cast through the scene.
Over the years, however, the expectations have risen substantially when it comes to image quality. Computing pictures which are indistinguishable from real footage requires accurate simulation of light transport, which is most often performed using some variant of Monte Carlo path tracing. Unfortunately this paradigm requires random memory accesses to the whole scene and does not lend itself well to a rasterisation approach at all.
Manuka is both a uni-directional and bidirectional path tracer and encompasses multiple importance sampling (MIS). Interestingly, and importantly for production character skin work, it is the first major production renderer to incorporate spectral MIS in the form of a new ‘Hero Spectral Sampling’ technique, which was recently published at Eurographics Symposium on Rendering 2014.
Manuka propose a shade-before-hit paradigm in-stead and minimise I/O strain (and some memory costs) on the system, leveraging locality of reference by running pattern generation shaders before we execute light transport simulation by path sampling, “compressing” any bvh structure as needed, and as such also limiting duplication of source data.
The difference with reyes is that instead of baking colors into the geometry like in Reyes, manuka bakes surface closures. This means that light transport is still calculated with path tracing, but all texture lookups etc. are done up-front and baked into the geometry.The main drawback with this method is that geometry has to be tessellated to its highest, stable topology before shading can be evaluated properly. As such, the high cost to first pixel. Even a basic 4 vertices square becomes a much more complex model with this approach.
Manuka use the RenderMan Shading Language (rsl) for programmable shading [Pixar Animation Studios 2015], but we do not invoke rsl shaders when intersecting a ray with a surface (often called shade-on-hit). Instead, we pre-tessellate and pre-shade all the input geometry in the front end of the renderer.
This way, we can efficiently order shading computations to sup-port near-optimal texture locality, vectorisation, and parallelism. This system avoids repeated evaluation of shaders at the same surface point, and presents a minimal amount of memory to be accessed during light transport time. An added benefit is that the acceleration structure for ray tracing (abounding volume hierarchy, bvh) is built once on the final tessellated geometry, which allows us to ray trace more efficiently than multi-level bvhs and avoids costly caching of on-demand tessellated micropolygons and the associated scheduling issues.For the shading reasons above, in terms of AOVs, the studio approach is to succeed at combining complex shading with ray paths in the render rather than pass a multi-pass render to compositing.
For the Spectral Rendering component. The light transport stage is fully spectral, using a continuously sampled wavelength which is traced with each path and used to apply the spectral camera sensitivity of the sensor. This allows for faithfully support any degree of observer metamerism as the camera footage they are intended to match as well as complex materials which require wavelength dependent phenomena such as diffraction, dispersion, interference, iridescence, or chromatic extinction and Rayleigh scattering in participating media.
As opposed to the original reyes paper, we use bilinear interpolation of these bsdf inputs later when evaluating bsdfs per pathv ertex during light transport4. This improves temporal stability of geometry which moves very slowly with respect to the pixel raster
In terms of the pipeline, everything rendered at Weta was already completely interwoven with their deep data pipeline. Manuka very much was written with deep data in mind. Here, Manuka not so much extends the deep capabilities, rather it fully matches the already extremely complex and powerful setup Weta Digital already enjoy with RenderMan. For example, an ape in a scene can be selected, its ID is available and a NUKE artist can then paint in 3D say a hand and part of the way up the neutral posed ape.
We called our system Manuka, as a respectful nod to reyes: we had heard a story froma former ILM employee about how reyes got its name from how fond the early Pixar people were of their lunches at Point Reyes, and decided to name our system after our surrounding natural environment, too. Manuka is a kind of tea tree very common in New Zealand which has very many very small leaves, in analogy to micropolygons ina tree structure for ray tracing. It also happens to be the case that Weta Digital’s main site is on Manuka Street.
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Aputure AL-F7 – dimmable Led Video Light, CRI95+, 3200-9500K
High CRI of ≥95
256 LEDs with 45° beam angle
3200 to 9500K variable color temperature
1 to 100% Stepless Dimming, 1500 Lux Brightness at 3.3′
LCD Info Screen. Powered by an L-series battery, D-Tap, or USB-C
Because the light has a variable color range of 3200 to 9500K, when the light is set to 5500K (daylight balanced) both sets of LEDs are on at full, providing the maximum brightness from this fixture when compared to using the light at 3200 or 9500K.
The LCD screen provides information on the fixture’s output as well as the charge state of the battery. The screen also indicates whether the adjustment knob is controlling brightness or color temperature. To switch from brightness to CCT or CCT to brightness, just apply a short press to the adjustment knob.
The included cold shoe ball joint adapter enables mounting the light to your camera’s accessory shoe via the 1/4″-20 threaded hole on the fixture. In addition, the bottom of the cold shoe foot features a 3/8″-16 threaded hole, and includes a 3/8″-16 to 1/4″-20 reducing bushing.