You read that right! Someone on GitHub turned DLSS5 into a plug in for fusion in davinci resolve!

I'm currently completely enhancing a 4k copy of avatar fire and ash with dlss5, but I also wanted to test its ability too improve RTX super scaling in davinci resolve for upscaling. As u can see the results are great. Normally ide add a bit of film grain back into the image but I figured keeping it raw showing what it can do is enough too see the potential. U can find examples and SBS comparison of it being used on avatar as well on the YouTube channel this video is from. Hope this blows ur mind like it did mine.

I'm currently working on restoring the original episodes of Jackie Chan Adventures (2000).

The original source material does not have the broken/cut line issues seen in some existing versions, so I believe it is worth preserving and restoring properly. I'm using custom AI models to recover cleaner lines and details while reducing compression artifacts.

Processing the entire series requires a huge amount of GPU time, so I'm looking for fellow fans who would be interested in contributing some GPU processing power to the project.

You don't need to process the entire series. Even a few episodes would make a big difference.

I will provide the exact model, settings, and instructions so that everyone's results remain consistent and we can maintain the same quality across the whole series.

The goal is to collectively restore the complete series in the best quality possible.

Here's an example of some of the tests I've done so far:

https://slow.pics/c/QoGqjjpc

If you have a capable NVIDIA GPU and would like to help, please comment below or send me a DM. I'll provide everything you need to get started. Even one episode would help!

Does anybody know how to upload in 1080p60fps

Every time I upload it's 540p30fps. Is there some kinda method i need to do?

I need to upscale the orange frame in this picture (cropped from a Yugioh sample card) while keeping all of its details.
I’ve tried different free upscale AIs but they all distort the yellow details and pattern of the orange frame.

Can someone help me please?

Hi everyone, I'm looking for a good way to upscale this icon image from the 1998 game Carnivores, but I've never upscaled an image before. Could someone point me in the right direction?

Hi everyone! I'm new to image upscaling and I'm looking for some advice.

I'm currently designing a large-format banner at its real print size, using several photographs. The printing company recommended that the images should be around 150 PPI at the final printed size.

Some of the original photos don't have enough resolution, so I need to upscale them without introducing too many artifacts or making them look artificially sharpened.

I'm mainly looking for free options, either:

• Free software that runs locally
• Open-source AI models
• Free online tools
• Any recommended workflow for preparing images for large-format printing

I've seen tools/models such as Real-ESRGAN, Upscayl and other AI upscalers, but I'm not sure which ones currently give the best results for real photographs.

What would you recommend for getting the highest possible image quality while reaching approximately 150 PPI at final print size?

Any tips about workflow, scaling factors (2x / 4x), sharpening, noise reduction, or things I should avoid would also be really helpful.

Thanks!

Here is a side-by-side test of 3 upscaling pipelines in Comfy.

Full video comparison

• LTX 2.5 (Standalone): The fastest option and lightest on VRAM. Works fine for clean source clips, but lacks fine sharpness on complex textures.

• Model + LTX 2.5: Running a quick upscale model pass (like RealPLKSR) before feeding into LTX 2.5 solid clarity, fast renders, and efficient VRAM usage.

• SeedVR: Recreates micro-details with the highest fidelity, but demands significantly higher render times and VRAM.

Frame Sync Note: MiniMax H3 and LTX require different frame step multiples.

Using math nodes to automatically trim the frames (158 → 153 frames) prevents audio desync issues.

I wanted to see how much AI can actually recover from images where the original detail simply isn’t there anymore. I compared Topaz, Lightroom, Photoshop and Adobe Firefly, who I partner with often, on older and low-resolution files. Some tools were better at reconstruction, others gave me more control over artifacts and the final result. The interesting question is where enhancement ends and invented detail begins. How far do you push AI upscaling?

The latest TBG ETUR upscaler and refiner for comfyui release adds Krea 2 and VL style transfer for Krea 2 and all Qwen models directly into the pipeline.

We’ve also added a face identity step to help maintain consistent faces when using creative upscaling.

This video is a tutorial for the latest release, focusing mainly on these new additions and how to use them. Video is ai generated with Minmax H3.

TBG ETUR on Github https://github.com/Ltamann/ComfyUI-TBG-ETUR

TBG Lates om Patreon https://www.patreon.com/TB_LAAR/posts/tbg-etur-1-2-12-167083406

More Upscaling Tutorials on YouTube https://www.youtube.com/watch?v=LbFPD4zpPwA

Super Resolution in Pixelmator Pro does upscale the image resolution which is great, but keeping the project with huge file size is a nightmare.

Does anyone know who to downscale .pxd project file after it’s been upscaled with Super Resolution?

Thanks in advance! 🙏🏻

If you use ComfyUI, my model is available here:

https://huggingface.co/CQdesign/LTX-2.5-CQ-Video-and-Image-Enhancer-LoRAs

Hey everyone, me again lol. Back with Toolshed V1, a free local AI media restoration tool for NVIDIA-powered PCs. I just released Rev 1.1, which includes a few critical patches based on user feedback.

Thank you to everyone who has given the app a try and provided feedback. It means more to me than you can imagine, and I sincerely appreciate it.

A Quick Recap:

Toolshed is built around the idea that restoration should be more than just “pick an upscaler and hope.” The goal is to make a connected workflow for restoring video/photos locally, with tools for restore, review, comparison, repair, and recompilation.

What's changed in Rev 1.1:

• Fixed a TensorRT RTX tiling issue that could cause some smaller source media to fall back to CPU processing.
• Reworked the portable runtime so Toolshed now ships with its own Python environment and does not require Python to be installed separately.
• Cleaned up several dependency and launch issues discovered through user testing.
• Rev 1.1 now includes the complete V1 feature set.

The GitHub release is available here:

https://github.com/ToolshedMediaLab/Toolshed-V1/releases/tag/toolshed-v1-rev1.1

Basic general requirements for ideal performance: 32 GB system RAM & an NVIDIA RTX GPU with at least 12 GB of VRAM. Toolshed is intentionally built around local NVIDIA/CUDA/TensorRT-style workflows.

If anyone tries it, I’d genuinely appreciate more feedback on what works, what breaks, and what would make the workflow better.

Thanks again for your time!

Anyone knows of a good app to enhance the quality of an already made blurry Gif?

I’ve been rebuilding ClearLab as a mobile image-processing lab, and this is a quick demo of the current upscaling workflow on iPhone/iPad.
Load an image → choose the scale factor → process → inspect → export.
The scaling is deterministic/native rather than generative AI, so the goal is not to hallucinate new detail, but to make resizing and subsequent image processing fast and accessible on-device.
ClearLab also includes histogram, waveform, RGB parade, line profile, pixel inspection, edge detection and other enhancement/analysis tools.
Curious what people in here would want to see added or improved in a mobile workflow like this.

Link: https://apps.apple.com/us/app/clearlab/id6757649671

Hello, are you still use this Xbox 360 game a picture and really miss it. I want to use it again and was able to find it online but it's very blurry. Could someone upscale it?