For the past 2 years, I’ve been stalked on reddit, 4chan, tumblr and various other websites. These people have a whole forum dedicated to me, spreading lies about me, and stalking my friends and family in efforts to “finding my nudes” which do not EXIST! First of all its CHILD PORNOGRAPHY (real or fake) and second of all its just not what kind of person I am. So what these people ended up doing was cutting my face off of a selfie (from when I was 15 years old!) and photoshoppingit onto a naked body to make it seem like its me.
I was horrified when I saw the picture floating around tumblr with thousands of reblogs, my image is virtually ruined. I felt panicked thinking what if my parents or school saw that and thought it was real!? how could they ever get that image of me out of their head? How can I?
This misogynistic obsession with exposing young girls naked pictures needs to stop. I dont even know how to properly address this because it freaks me out, but I just want to make this post to warn people that this could happen to anyone, be careful what you see and post online. I don’t know what to do at this point except put this out there to clear my name.
I started researching deepfake detection method after IG video published, an approach that can objectively examine a clip without any bias. After researching published deepfake detection papers, I started to build the code based on one of the published deepfake detection models. It took me 2 days to have the first result generated without fine-tuning. The result was published on Weibo and banned 6 hours after posting. Based on the feedback from other experts, I refined the model to have the second version published here, with a detailed explanation of the method.
I retrained the model with raw/uncompressed video, and increased the training samples. The final output reduced false negative rate, leading to a more accurate reading.
The algorithm classifies each frame of video along with confidence values. The green box with 90% value, means the model classified this frame as real with 90% confidence. If the box shows red with 90% value, it means the model classified this frame as fake with 90% confidence.
I compared the IG video with zzh’s previous real-person interviews. The video showing my results are below and includes the ZZH IG video first and then two confirmed real interview clips with him. The confirmed real-person interviews were included to show what the model outputs when the video is real. After running the videos through the model, the results showed that where more facial expression was present, more fake frames were detected.
The below chart shows the detection result with confidence value within a video. When the algorithm detects the frame as being “real”, there will be a positive confidence value. When it detects the frame as being “fake”, there will be a negative confidence value.
This is the chart of the confidence values detected for the IG video. Note that the results fluctuate with high volatility between -100 to 100
This is the chart of the confidence values for the first confirmed real interview video used in the video clip. The results are between 90-92 with minor volatility
As comparison, I run the model through two known deep fake videos. Result is shows in a separate post.
The model used in this simulation is called “Xception”. The paper describing the model can be found here: https://arxiv.org/abs/1901.08971
The model was trained via Faceforensics++ data which is collected by the Visual Computing Group. I downloaded 800 raw videos (200 real + 600 fake) covering 3 state-of-art video manipulation techniques such as deepfakes, faceswap and face2face.
Data are divided into training, testing, and cross-validation group. Then I took 101 face images from each video and pre-processed every image by applying a face tracker algorithm that detects face area pixels. Based on those classified videos, the AI model will learn how to distinguish between a manipulated video and a real video. It is similar to the process of a baby learning the difference between an apple and orange, the model will classify fake and real along with confidence values on each frame of the video.
At present, Deepfake and Deepfake detection technology is progressing simultaneously. A good model can detect a modified video made by a less trained/outdated deepfake model, but a better deepfake model can also fool a good trained detection model. No technology is perfect and it is possible for a very good modified video to escape detection given current Deepfake detection technology.
I would really like to see David Prowse’ face inserted instead of Sebastian Shaw’s in Vader death scene in Return of the Jedi using deepfake technology.
A WIP of Thrawn X Sabine Wren. From the Tudors. It’s not the correct uniform, but Sabine Wren was face swapped with Natasha Liu Bordizzo’s face and then worked by FaceApp, Photoshop Fix, and Express. Sabine’s hair has color and is long. It is how these programs operate.
This is the ship SWAG77 does for fanfiction; to learn more, visit our blog.
People can choose whatever they want to ship. I’m a pro shopper. Knock yourselves out. But I’m just doing my ship for fun and without expectations. I’ll still do it despite what someone says about it. And while Thrawn’s uniform is an early canon version from Star Wars Thrawn Ascendancy, it was used for position, NOT a story statement.
When Thrawn meets Sabine, they are both adults, and both consented. If that’s your foul defamatory as slander judgy accusation, there is no pedo here. This fanfic is about consent.
If you don’t want to “get” it, that’s on you. Not me.
What do you think? I’m not an artist but an art critic. I’d say this artist is crazy and has a poor idea about me with that smirk. But yes, that is my age… Not in my 30s and above that decade. 2 scores.
There are hardly any new pictures of Natasha Liu Bordizzo as Sabine Wren. Someday there will be. But to get an idea, deepfake technology can be used to create images.
This image was create Reface, FaceApp, Photoshop Express all on a mobile phone (iPhone11Pro).
Several iterations were created for the final image. It is not perfect and a WIP as there were walls hit. This image might be…
“I want nothing of his foolishness within my boudoir. He knows better than–” Door opens wide as she see him entering carrying his cap. She glares and yells. “OSIK! Go away!” But he ignores her with a huge grin as his eyes gleam.
