The Gaming Restoration | Resident Evil 4: Separate Ways Cutscenes (Remastered in 1080p using AI Machine Learning) @TheGamingRestoration | Uploaded 5 years ago | Updated 10 hours ago
Resident Evil 4: Separate Ways - Cutscene Compilation
Remastered in 1080p using ESRGAN [AI Machine Learning]
2:30 Chapter 1: Ring the Church Bell
5:39 Chapter 2: Rescue Luis
13:16 Chapter 3: Retrieve the Sample
18:58 Chapter 4: Stop Leon's Assassination
22:51 Chapter 5: Obtain the Sample
ESRGAN is an AI Neural Network software that is capable of upscaling and reconstructing low-resolution images, while retaining most of their elements and details intact.
I took the original video files from the Resident Evil 4 PS2 disk, and used ESRGAN to upscale them 4 times their original resolution.
This time I used 3 different training models: alsa64's denoising model [JPG (0-20%)]; the Manga109 training model; and my own, which I made using the Dolphin Emulator (I took HD screenshots of several cutscenes from the main campaign, and used them to
train a new model).
Original resolution: 512x336 / 320x208
ESRGAN Upscale: 2048x1344 / 1280x832 --) 2560x1440
(Upscaled to 1440p with lanczos to preserve video quality on YouTube)
Next goal: Replacing the FMVs from the PC version with these ones.
Resident Evil 4: Separate Ways - Cutscene Compilation
Remastered in 1080p using ESRGAN [AI Machine Learning]
2:30 Chapter 1: Ring the Church Bell
5:39 Chapter 2: Rescue Luis
13:16 Chapter 3: Retrieve the Sample
18:58 Chapter 4: Stop Leon's Assassination
22:51 Chapter 5: Obtain the Sample
ESRGAN is an AI Neural Network software that is capable of upscaling and reconstructing low-resolution images, while retaining most of their elements and details intact.
I took the original video files from the Resident Evil 4 PS2 disk, and used ESRGAN to upscale them 4 times their original resolution.
This time I used 3 different training models: alsa64's denoising model [JPG (0-20%)]; the Manga109 training model; and my own, which I made using the Dolphin Emulator (I took HD screenshots of several cutscenes from the main campaign, and used them to
train a new model).
Original resolution: 512x336 / 320x208
ESRGAN Upscale: 2048x1344 / 1280x832 --) 2560x1440
(Upscaled to 1440p with lanczos to preserve video quality on YouTube)
Next goal: Replacing the FMVs from the PC version with these ones.
![Primal [1440p] PCSX2 1.5.0 dev, Gameplay (Custom PCSX2 Build - Download Link)](https://i.ytimg.com/vi/pAUHH90hudU/hqdefault.jpg "Primal [1440p] PCSX2 1.5.0 dev, Gameplay (Custom PCSX2 Build - Download Link)
PCSX2 1.5.0-20190109200529 - compiled on Jan 13 2019
OS: Linux 4.20.1-zen1-1-zen
Physical RAM: 6GB
CPU: Intel(R) Core(TM) i7-2600 CPU @ 3.40GHz
GPU: Nvidia GT 1030 2GB (GDDR5)
GsdX OpenGL (Hardware) – Rendered at 6x Native Internal Resolution (3840x2688 [cropped front buffer: 2400x2688]) – Disabled “texture cache memory garbage cleanup” code (more info in the video description)
Cutsom External shader conf
PCSX2 Config
MTVU Off
GSdx
OpenGL (Hardware)
Interlacing Auto
Internal Resolution 6x Native (~2160p 4K) (3840x2688 [cropped front buffer: 2400x2688])
Disabled “texture cache memory garbage cleanup” code.
USE THIS CUSTOM BUILD TO PLAY PRIMAL: https://drive.google.com/file/d/1QlUGbZYKq7ep0c72gLNF1KdbTKGnjgNi
Automatic CRC Level Partial (OpenGL Recommended)
Mipmapping (Insert): Basic (Fast)
Accurate Date: Fast (Default)
Blending Unit Accuracy High (Recommended high-end PC)
Shader Config (GSdx.fx)
UHQ_FXAA On
Gaussian Filtering On
Lanczos Scaler On
High Quality Blended Bloom On
RGB Gamma Correction On
Pixel Vibrance On (Vibrance 0.20)
Bicubic Texture Unsharpen Mask On (SharpenStrength 2.00; SharpenClamp 0.500; SharpenBias 4.00)
S-Curve Scene Contrast Enhancement On")
![[PCSX2 VS PS4 PRO] Okami VS Okami HD](https://i.ytimg.com/vi/qK3hVAifPk8/hqdefault.jpg "[PCSX2 VS PS4 PRO] Okami VS Okami HD
PS4 Pro footage recorded by Gamersyde at native 4K 60FPS.
PS2 footage recorded using PCSX2 1.5.0-20171210213700
-English translation by Crazycatz00.
-60fps hacks by asasega
-GSdx OpenGL (Hardware) → 8X Native Resolution (4096x4096)
-GSdx external shaders + Shader Boost + MTVU
PC SPECS
OS: Linux 4.14.5-1-ARCH x86_64
Physical RAM: 6GB
CPU: Intel® Core(TM) i7-2600 CPU @ 3.40GHz
GPU: Nvidia GT 1030 2GB (NOT recorded in real-time)
21068223.pnach
gametitle=Okami (NTSC-U)
comment=Force 60 FPS
//60 fps
patch=1,EE,0067E505,extended,00000001")
![The Getaway [60FPS HACK] PCSX2 1.5.0 dev, Cutscenes/Gameplay](https://i.ytimg.com/vi/rBqbu8J-pfI/hqdefault.jpg "The Getaway [60FPS HACK] PCSX2 1.5.0 dev, Cutscenes/Gameplay
60FPS footage of The Getaway, recorded on the PCSX2 emulator with a 60fps hack.
E21404E2.pnach
gametitle=The Getaway
comment=Force 60 FPS
//60 fps
patch=1,EE,201F10E8,extended,1000000B")
![Dogs Life Intro (Remastered in 1440p using AI Machine Learning) [Impressive Results]](https://i.ytimg.com/vi/rYWkI9CPtTE/hqdefault.jpg "Dogs Life Intro (Remastered in 1440p using AI Machine Learning) [Impressive Results]
Dogs Life Opening FMV
Remastered in 1440p using ESRGAN [AI Machine Learning]
ESRGAN is an AI Neural Network software that is capable of upscaling and reconstructinglow-resolution images, while retaining most of their elements and details intact.
I took the original video file from the Dogs Life PS2 disk, and used ESRGAN withthe Manga109 training model to upscale the video 4 times its original resolution.
Original resolution: 720x480
ESRGAN Upscale: 2880x1920 → 2560x1440")
