All posts by jnack

Runway reskins rock

Another day, another set of amazing reinterpretations of reality. Take it away Nathan…


…and Bilawal:

Mystic structure reference: Dracarys!

I love seeing the Magnific team’s continued rapid march in delivering identity-preserving reskinning

This example makes me wish my boys were, just for a moment, 10 years younger and still up for this kind of father/son play. 🙂

Behind the scenes: AI-augmented animation

“Rather than removing them from the process, it actually allowed [the artists] to do a lot more—so a small team can dream a lot bigger.”

Paul Trillo’s been killing it for years (see innumerable previous posts), and now he’s given a peek into how his team has been pushing 2D & 3D forward with the help of custom-trained generative AI:”

Charmingly terrible AI-made infographics

A passing YouTube vid made me wonder about the relative strengths of World War II-era bombers, and ChatGPT quickly obliged by making me a great little summary, including a useful table. I figured, however, that it would totally fail at making me a useful infographic from the data—and that it did!

Just for the lulz, I then ran the prompt (“An infographic comparing the Avro Lancaster, Boeing B-17, and Consolidated B-24 Liberator bombers”) through a variety of apps (Ideogram, Flux, Midjourney, and even ol’ Firefly), creating a rogue’s gallery of gibberish & Franken-planes. Check ’em out.

Surrealism blooms through Pika

Check out this delightful demo:

Individual steps, as I understand them:

  • Generate image (in this example, using Google Imagen).
  • Apply background segmentation.
  • Synthesize a new background, and run what I think is a fine-tuned version of IC-Light (using Stable Diffusion) to relight the entire image, harmonizing foreground/background. Note that identity preservation (face shape, hair color, dress pattern, etc.) is very good but not perfect; see changes in the woman’s hair color, expression, and dress pattern.
  • Put the original & modified images into Pika, then describe the desired transformation (smooth transition, flowers growing, clouds moving, etc.).

NeRFtastic BAFTAs

The British Academy Film Awards have jumped into a whole new dimension to commemorate the winners of this year’s awards:

The capturing work was led by Harry Nelder and Amity Studio. Nelder used his 16-camera rig to capture the recent winners. The reconstruction software was a combination of a cloud-based platform created by Nelder, which is expected to be released later this year, along with Postshot. Nelder further utilized the Radiance Field method known as Gaussian Splatting for the reconstruction. A compilation video of all the captures, recently posted by BAFTA, was edited by Amity Studio

[Via Dan Goldman]

Lego together creative AI blocks in Flora

Looks promising:

Their pitch:

  • Create workflows, not just outputs. Connect Blocks to shape, refine, and scale your creative process.
  • Collaborate in real time. Work like you would in Figma, but for AI-powered media creation.
  • Discover & clone workflows. Learn from top creatives, build on proven systems and share generative workflows inside FLORA’s Community.

Sigma BF: Clean AF

Refreshingly simple design!

Is it for me? Dunno: lately the only thing that justifies shooting with something other than my phone is a big, fast zoom lens, and I don’t know whether pairing such a thing with this slim beauty would kinda defeat the purpose. Still, I must know more…

Here’s a nice early look at the cam plus a couple of newly announced lenses:

Perhaps image-to-3D was a mistake…

Behold the majesty (? :-)) of CapCut’s new “Microwave” filter (whose name makes more sense if you listen with sound on):

https://youtube.com/shorts/bshQXczbZdw?si=aFwvtgs-fKf2wl8x

As I asked Bilawal, who posted the compilation, “What is this, and how can I know less about it?”

EditIQ edits single long shots into multiples virtual shots

Check it out (probably easier to grok by watching vs. reading a description):

From the static camera feed, EditIQ initially generates multiple virtual feeds, emulating a team of cameramen. These virtual camera shots termed rushes are subsequently assembled using an automated editing algorithm, whose objective is to present the viewer with the most vivid scene content.

Controlling video generation with simple props

Tired: Random “slot machine”-style video generation
Inspired: Placing & moving simple guidance objects to control results:
Check out VideoNoiseWarp:

Analog meets AI in the papercraft world of Karen X Cheng

Check out this fun mixed-media romp, commissioned by Adobe:

And here’s a look behind the scenes:

A cool Firefly image->video flow

For the longest time, Firefly users’ #1 request was to use images to guide composition of new images. Now that Firefly Video has arrived, you can use a reference image to guide the creation of video. Here’s a slick little demo from Paul Trani:

Titles: Severance Season 2

Building on the strong work from the previous season,

Berlin’s Extraweg have created… a full-blown motion design masterpiece that takes you on a wild ride through Mark’s fractured psyche. Think trippy CGI, hypnotic 3D animations, and a surreal vibe that’ll leave you questioning reality. It’s like Inception met a kaleidoscope, and they decided to throw a rave in your brain. [more]

Google Photos will flag AI-manipulated images

These changes, reported by Forbes, sound like reasonable steps in the right direction:

Starting now, Google will be adding invisible watermarks to images that have been edited on a Pixel using Magic Editor’s Reimagine feature that lets users change any element in an image by issuing text prompts.

The new information will show up in the AI Info section that appears when swiping up on an image in Google Photos.

The feature should make it easier for users to distinguish real photos from AI-powered manipulations, which will be especially useful as Reimagined photos continue to become more realistic.

DeepSeek meets Flux in Krea Chat

Conversational creation & iteration is such a promising pattern, as shown through people making ChatGPT take images to greater & greater extremes:


But how do we go from ironic laughs to actual usefulness? Krea is taking a swing by integrating (I think) the Flux imaging model with the DeepSeek LLM:

It doesn’t yet offer the kind of localized refinements people want (e.g. “show me a dog on the beach,” then “put a hat on the dog” and don’t change anything outside the hat area). Even so, it’s great to be able to create an image, add a photo reference to refine it, and then create a video. Here’s my cute, if not exactly accurate, first attempt. 🙂

A mind-blowing Gemini + Illustrator demo

Wow—check out this genuinely amazing demo from my old friend (and former Illustrator PM) Mordy:

In this video, I show how you can use Gemini in the free Google AI Studio as your own personal tutor to help you get your work done. After you watch me using it to learn how to take a sketch I made on paper to recreating a logo in Illustrator, I promise you’ll be running to do the same.

MatAnyone promises incredible video segmentation

What the what?

Per the paper,

We propose MatAnyone, a robust framework tailored for target-assigned video matting. Specifically, building on a memory-based paradigm, we introduce a consistent memory propagation module via region-adaptive memory fusion, which adaptively integrates memory from the previous frame. This ensures semantic stability in core regions while preserving fine-grained details along object boundaries. 

Premiere Pro now lets you find video clips by describing them

I love it: nothing too fancy, nothing controversial, just a solid productivity boost:

Users can enter search terms like “a person skating with a lens flare” to find corresponding clips within their media library. Adobe says the media intelligence AI can automatically recognize “objects, locations, camera angles, and more,” alongside spoken words — providing there’s a transcript attached to the video. The feature doesn’t detect audio or identify specific people, but it can scrub through any metadata attached to video files, which allows it to fetch clips based on shoot dates, locations, and camera types. The media analysis runs on-device, so doesn’t require an internet connection, and Adobe reiterates that users’ video content isn’t used to train any AI models.

Celebrating the skate art of Jim Phillips

If you’re like me, you may well have spent hours of your youth lovingly recreating the iconic designs of pioneering Santa Cruz artist Jim Phillips. My first deck was a Roskopp 6, and I covered countless notebook covers, a leg cast, my bedroom door, and other surfaces with my humble recreations of his work.

That work is showcased in the documentary “Art And Life,” screening on Thursday in Santa Cruz. I hope to be there, and maybe to see you there as well. (To this day I can’t quite get over the fact that “Santa Cruz” is a real place, and that I can actually visit it. Growing up it was like “Timbuktu” or “Shangri-La.” Funny ol’ world.)

Gemini turns photos into interactive simulations (!)

Check out this wild proof of concept from Trudy Painter at Google, and click into the thread for details.

Quick fun with Krea, Flux, custom training, and 3D

Putting the proverbial chocolate in the peanut butter, those fast-moving kids at Krea have combined custom model training with 3D-guided image generation. Generation is amazingly fast, and the results are some combo of delightful & grotesque (aka “…The JNack Story”). Check it out:

“The Heist,” conjured entirely in Google Veo

Here’s another interesting snapshot of progress in our collective speedrun towards generative storytelling. It’s easy to pick on the shortcomings, but can you imagine what you’d say upon seeing this in, say, the olden times of 2023?

The creator writes,

Introducing The Heist – Directed by Jason Zada. Every shot of this film was done via text-to video with Google Veo 2. It took thousands of generations to get the final film, but I am absolutely blown away by the quality, the consistency, and adherence to the original prompt. When I described “gritty NYC in the 80s” it delivered in spades – CONSISTENTLY. While this is still not perfect, it is, hands down, the best video generation model out there, by a long shot. Additionally, it’s important to add that no VFX, no clean up, no color correction has been added. Everything is straight out of Veo 2. Google DeepMind

SynthLight promises state-of-the-art relighting

Here’s a nice write-up covering this paper. It’ll be interesting to dig into the details of how it compares to previous work (see category). [Update: The work comes in part from Adobe Research—I knew those names looked familiar :-)—so here’s hoping we see it in Photoshop & other tools soon.]

Krea introduces realtime 3D-guided image generation

Part 9,201 of me never getting over the fact we were working on stuff like this 2 years ago at Adobe (modulo the realtime aspect, which is rad) & couldn’t manage to ship it. It’ll be interesting to see whether the Krea guys (and/or others) pair this kind of interactive-quality rendering with a really high-quality pass, as NVIDIA demonstrated last week using Flux.

Creating a 3D scene from text

…featuring a dose of Microsoft Trellis!

More about Trellis:

Powered by advanced AI, TRELLIS enables users to create high-quality, customizable 3D objects effortlessly using simple text or image prompts. This innovation promises to improve 3D design workflows, making it accessible to professionals and beginner alike. Here are some examples:

Adobe demos generation of video with transparency

Exciting!

From the project page:

Alpha channels are crucial for visual effects (VFX), allowing transparent elements like smoke and reflections to blend seamlessly into scenes. We introduce TransPixar, a method to extend pretrained video models for RGBA generation while retaining the original RGB capabilities. […] Our approach effectively generates diverse and consistent RGBA videos, advancing the possibilities for VFX and interactive content creation.

NVIDIA + Flux = 3D magic

I may never stop being pissed that that the Firefly-3D integration we previewed nearly two years ago didn’t yield more fruit, at least on my watch:

The world moves on, and now NVIDIA has teamed up with Black Forest Labs to enable 3D-conditioned image generation. Check out this demo (starting around 1:31:48):

Details:

For users interested in integrating the FLUX NIM microservice into their workflows, we have collaborated with NVIDIA to launch the NVIDIA AI Blueprint for 3D-guided generative AI. This packaged workflow allows users to guide image generation by laying out a scene in 3D applications like Blender, and using that composition with the FLUX NIM microservice to generate images that adhere to the scene. This integration simplifies image generation control and showcases what’s possible with FLUX models.

Skillful Lovecraftian horror

The Former Bird App™ is of course awash in mediocre AI-generated video creations, so it’s refreshing to see what a gifted filmmaker (in this case Ruairi Robinson) can do with emerging tools (in this case Google Veo)—even if that’s some slithering horror I’d frankly rather not behold!

Happy New Year!

Happy (very slightly belated) new year, everyone! Thanks for continuing to join me on this wild, sometimes befuddling, often exhilarating journey into our shared creative future. Some good perspective on the path ahead:

Bonus wisdom from F. Scott Fitzgerald:

New AI-powered upscalers arrive

Check out the latest from Topaz:


Alternately, you can run InvSR via Gradio: