Official Link : Nvidia docs

NVIDIA RTX 2-Pass Upscaler (4GB VRAM + 8GB RAM)

Post:

Hi everyone!

Recently, while working on AI videos with the LTX2.3 model, I started thinking a lot about upscaling efficiency, so I made my own RTX Upscale node for ComfyUI.

In the existing ComfyUI setup, most workflows mainly used Video Super Resolution (VSR), but NVIDIA RTX upscaling actually has four different options. I implemented all four of them in this node.

After testing it myself, I honestly no longer feel a need to subscribe to Topaz AI.

- DeBlur: The most effective option for sharpening blurry videos, especially AI-generated videos.

- DeNoise: Helps clean up noisy footage. For AI videos, I recommend using it selectively.

- High Bitrate: Good for improving the quality of cleaner source videos.

- Video Super Resolution (VSR): The standard method that was commonly used before.

The main idea I applied is a 2-step upscaling method.

First, DeBlur is used to sharpen the video, and then High Bitrate or VSR is applied as the second pass. In my tests, this produced much better results.

Performance and requirements:

- On an RTX 5090, upscaling a 512x512 video to 1024x1024 takes about 5 seconds.

- For Low RAM / Low VRAM environments, I made a Batch image workflow. With this method, most low-spec systems can usually finish the upscaling within about 1-2 minutes.

- When using the Batch image method, the requirement is around 10GB RAM and 4GB VRAM.

Existing NVIDIA RTX Super Resolution nodes were very difficult to install because the backend setup often caused errors. So I prepared an install_rtx_vfx helper to make the backend installation as close to one-click as possible.

Installation:

1. Open ComfyUI Manager → Custom Node Manager, then search for deno-custom-nodes and install it.
2. Important: Completely close ComfyUI before running the installer. If ComfyUI is still running, the installation may not proceed.
3. Go to ComfyUI/custom_nodes/deno-custom-nodes/tools.
4. Run install_rtx_vfx.bat → wait for the installation complete message, then close the window. It usually takes about 30 seconds to 1 minute.
5. Restart ComfyUI and run the Deno RTX Video Super Resolution (2 Pass) node.

For detailed usage, please check the tutorial and workflow links below.

Link : WorkFlow

Link : Tutorial

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The DENO RTX Video Super Resolution update is currently being rolled out to ComfyUI Manager / Registry, so it may take a few hours before it appears for everyone. If you want to test it early, please follow the manual installation steps below.

First, completely close ComfyUI. This means closing not only the browser tab, but also the ComfyUI command window, cmd, PowerShell, or any terminal window that is running ComfyUI.

Download the installer from the official DENO GitHub repository:

https://github.com/Deno2026/comfyui-deno-custom-nodes/raw/refs/heads/main/tools/install_rtx_vfx_bat.zip

After downloading the zip file, extract it first. Do not run the .bat file directly from inside the zip file.

After extraction, you will see this file:

install_rtx_vfx.bat

Copy or move this file into the tools folder of your installed DENO custom nodes:

ComfyUI\custom_nodes\deno-custom-nodes\tools\

For example, the final location should look similar to this:

D:\ComfyUI\custom_nodes\deno-custom-nodes\tools\install_rtx_vfx.bat

Important:

Do not run install_rtx_vfx.bat from your Downloads folder. It must be placed inside:

ComfyUI\custom_nodes\deno-custom-nodes\tools\

Once the file is in the correct tools folder, double-click install_rtx_vfx.bat to run it.

If Windows shows a security warning, click “More info” and then “Run anyway.”

When the installer shows the ComfyUI Python path, check that it points to the python_embeded\python.exe used by the ComfyUI you just closed. If the path looks correct, type:

Y

and press Enter.

This installer installs NVIDIA’s official nvidia-vfx Python package from NVIDIA’s official package server, pypi.nvidia.com. It does not download random DLL files.

When you see a green “INSTALL COMPLETE” message or “[OK] NVIDIA RTX VFX is installed,” the installation is complete.

After that, restart ComfyUI and search for:

(Deno) RTX Video Super Resolution

Notes:

- You need an NVIDIA RTX GPU.

- Please use the latest NVIDIA driver.

- macOS is not supported.

- If you do not have the folder ComfyUI\custom_nodes\deno-custom-nodes\tools, please update DENO custom nodes first through ComfyUI Manager or GitHub, then try again.

https://huggingface.co/Kijai/LTX2.3_comfy/blob/main/loras/LTX-2.3-OmniNFT-RL-Lora_bf16.safetensors

https://zghhui.github.io/OmniNFT/

I’ve been experimenting with LTX Director for LTX 2.3, and I think this workflow has a lot of potential.

Local I2V often feels like “make this one image wiggle”: same angle, small motion, maybe blinking or hair movement. But with LTX Director, using multiple images of the same character as key poses/camera angles inside one timeline feels much closer to shot direction or a tiny MV editor.

For this test, I used three source images of the same character with the same outfit/background, but different poses and camera angles. I included the original three images as well, so you can see what LTX Director was working from.

I also added a custom K-pop-style audio track with Custom Audio ON.

After a lot of tuning, it was able to handle:

- multi-image I2V

- smooth pose changes

- camera and face movement between poses

- cute performance gestures

- custom audio timing

- usable lip-sync

It’s still experimental. Hands can break, identity can drift, and transitions need careful prompting. But when the input images are consistent — same character, outfit, background, and style — it becomes much more dynamic than normal single-image I2V.

The most useful prompt idea for me was to treat the images as key poses of the same character, not separate people:

“Treat all images as the same character in different poses and camera angles. Preserve the same face, hairstyle, outfit, and background throughout. Move smoothly between the poses as one continuous close-up performance. Natural lip-sync to the custom audio vocals, clear visible mouth movement, soft blinking, small head tilts, cute gestures, subtle shoulder sway, light hair motion.”

This still needs more testing, but I think LTX Director could be really useful for AI idol clips, character PVs, surreal mascot videos, short music videos, and anything where local video generation needs more than one static angle

I was looking for performance benchmarks for the 5060Ti in a dual-GPU setup with Anima, but didn't find much. Hope this helps anyone looking for similar benchmarks for this specific hardware configuration.

Hardware & Software:

• GPUs: 2x RTX 5060Ti (OC +250/+2000) connected with pcie 4.0 x8
• Base Model: Anima v1.0 (HF)
• LoRA: Turbo LoRA (Civitai)
• Plugin: Raylight (GitHub)

Performance:

Resolution	Lora	Compile	ulysses	ring	Time (s)
1024x1024	ON	ON	1	2	3.8
1024x1024	ON	OFF	1	2	4.0
1024x1024	OFF	ON	1	2	21.4
1024x1024	OFF	OFF	1	2	23.5
----------	----	-------	-------	----	--------
1584x1584	ON	ON	1	2	7.9
1584x1584	ON	OFF	1	2	8.6
1584x1584	OFF	ON	1	2	ERR
1584x1584	OFF	OFF	1	2	ERR
1584x1584	OFF	ON	2	1	60.4
1584x1584	OFF	OFF	2	1	67.7
----------	----	-------	-------	----	--------
2048x2048	ON	ON	1	2	13.0
2048x2048	ON	OFF	1	2	14.5
2048x2048	OFF	ON	1	2	85.5
2048x2048	OFF	OFF	1	2	98.0
2048x2048	OFF	ON	2	1	105.1

*typo in workflow. Compile backend must be inductor, not cudagraphs (trigger err)
*workflow embedded into images

Good afternoon!

This is an update to my character generation workflow.

I was very pleased with the release of Anima-Base. It is quite flexible, has a lot of knowledge about characters, and generates different styles perfectly, and its turbo-lora gives quite high-quality results. However, I had to adjust a little to its behavior in img2img.

It used to be called "Sprite generator" referring to the images of characters from visual novels, but I decided that "Characters generator" would cause less confusion.

What's changed?

- Added the ability to specify indentations at the edges of the frame so that the character does not go beyond it.
- Improved tile upscaler using "anima-lllite-inpainting-v2"

Link

I was trying to get the HY World 2.0 / WorldMirror v2 and Sharp to work together in order to create something where a room could be explored. This is as about as far as I got. It's still missing something. *Scale button doesn't work with HY World nodes*. But yea, scaling the splat could help. Also, moving the camera really sucks, but I think that's the scale of the actual full splat just not being loaded properly, and I need to figure that out--either through the nodes available or creating my own (which would be hard af for me, not being a coder). If anyone has ideas, maybe I could throw a sheet together to see if Gemini can craft something. But regardless of all that, it's nice to finally get a panorama working in 360 viewable now.

Hey guys, I hope everyone is having great day.
I'm currently working on a project where I need to swap entire head between two images.
I have tried all sort of models, both open source and commercial and always got stuck between two priorities when one gets fulfilled the other doesn't.
First priority is that facial features should look so strong so that the person is so well recognizable as the source.

Second ( which is what most commercial models fail with), is that head should be resized to match target.

Third (not really strong priority semi priority) : adaption of body color or style, for example changing body color slightly to match head color of the source.

There other things like, Copying Facial emotions from target and head position, but these are not priorities. For commercial models I think i have tried every possible model out there.
And for open source models, I have tried bfs with Qwen basically have tried everything in this repo https://huggingface.co/Alissonerdx/BFS-Best-Face-Swap and it worked well for head size matching target, but facial expressions got so weak.
I was wondering can I find a workflow that fulfills my priorities very well, even if it requires large models size.

so I havent used SD since 2024, and im doing some files cleaning/updating.
are any of these models safe to delete and update?
in that case, which new/updated models should i replace these with?
thanks!

I built a Colab notebook that does facial expression copying using LivePortrait. You load a source image (contains a single face with any expression) and a target image (contains a single face whose expression is to be changed), adjust blend sliders, and it transfers the expression while preserving identity.

The notebook replaces LivePortrait's use of InsightFace for face detection with MediaPipe, so the entire pipeline is commercially permissive (MIT + Apache 2.0). It runs on a free Colab T4 GPU.

What it does: expression blend and head rotation blend with adjustable sliders, 512×512 upsampled output.

This is a demo for Face2FaceAI, an Android app I'm building that adds face reinsertion, asymmetry correction, template expressions, and other features — all running on-device. More at face2faceai.com.

The example shows before/after expression swap with face reinsertion (app feature)

Open in Colab | GitHub repo

Feedback welcome — this is my first public release.

https://lance-project.github.io/

https://github.com/bytedance/Lance

https://huggingface.co/bytedance-research/Lance

Have tested over 100+ videos across categories like:

1. Get Ready With Me (GRWM),
2. OOTD,
3. Lookbook videos

Still fails in 10-20% cases. Looking for early users to share feedback!

Hi friends.

While checking the latest version of Anima, I saw a message saying that Anima-Turbo will be released soon.

But does anyone know how long it might take? Does a base model, trained for a faster Turbo version, usually take a long time?

I'm asking out of ignorance. Because I'd like to know if models normally take many months to be released, or not.