Valorant player uses deep fake to apply gun cosmetic in video

Replacing the vanilla weapon skin in Valorant. Image by (phantomfake)
Replacing the vanilla weapon skin in Valorant. Image by (phantomfake)

Riot Games has been adding amazing and uniques weapon skins in Valorant regularly.

Currently, there are a lot of weapon skins in Valorant to choose from. A Valorant player was able to use neural networking to change the weapon skin in a video.

Valorant Weapon Skin deep fake

Riot Games have been maintaining a constant drip-feed of new weapon skins with unique looks and animations in Valorant. There are two primary ways to get a weapon skin. The in-game store lets players purchase either individually or as a part of a bundle collection. A recent addition, Night market, offers some skins at a discount.

The second way is via the battle pass. Every new act introduces a premium battle pass, which includes three sets of weapon skin collections as a reward for completing it.

Recently Redditor u/swegmesterflex posted his experience of replacing the vanilla weapon skin with a Singularity version in a small captured clip. He did it with the CycleGEN model. It is similar to replacing faces or part of a video using deep fakes.


The gun looks close to indistinguishable. However, there is a small shimmering shape around the gun model. This process does not include unique animations, as they are part of the weapon skins themselves.

This idea sparked a discussion of whether it is possible to replace the gun model in real-time, in-game. Redditor u/Darkfyre42 says that even though training a neural network in real-time is impossible, it might not be far-fetched to use an already trained neural network to replace a gun model. However, there would be a limitation of predetermined skin to be used.

Author u/swegmesterflex also adds that without quantizing, it might not be possible to train in real-time. However, it is possible to inference with neural networking in real-time, similar to Ray-tracing, Deep Learning Super Sampling, and RTX Voice. He further adds:

With quantization (using 8bit numbers instead of 32bit) what I'm doing could also be possible, though I've been struggling trying to learn the framework for it (Tensorflow lite does quantization, whereas I mainly use Pytorch). That being said, Pytorch does have a half-precision feature I've been trying to use.

u/swegmesterflex is currently looking for more gun models to have a larger dataset to draw from. He plans to develop an app, which anyone can download and change the gun model in their clips.

What u/swegmesterflex is developing might not be useful in-game. However, this experiment certainly pushes the boundary of machine-learning, neural networking, and technological development overall.

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Edited by Nikhil Vinod
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