This demonstrate large-scale text-to-video generation with a single neural function evaluation (1NFE) by using our proposed adversarial post-training technique. Our model generates 2 seconds of 1280×720 24fps videos in real-time
Jacob Bartlett argues that Swift, once envisioned as a simple and composable programming language by its creator Chris Lattner, has become overly complex due to Apple’s governance. Bartlett highlights that Swift now contains 217 reserved keywords, deviating from its original goal of simplicity. He contrasts Swift’s governance model, where Apple serves as the project lead and arbiter, with other languages like Python and Rust, which have more community-driven or balanced governance structures. Bartlett suggests that Apple’s control has led to Swift’s current state, moving away from Lattner’s initial vision.
The IPAdapter are very powerful models for image-to-image conditioning. The subject or even just the style of the reference image(s) can be easily transferred to a generation. Think of it as a 1-image lora. They are an effective and lightweight adapter to achieve image prompt capability for the pre-trained text-to-image diffusion models. An IP-Adapter with only 22M parameters can achieve comparable or even better performance to a fine-tuned image prompt model.
Once the IP-Adapter is trained, it can be directly reusable on custom models fine-tuned from the same base model.
The IP-Adapter is fully compatible with existing controllable tools, e.g., ControlNet and T2I-Adapter.
About 576 megapixels for the entire field of view.
Consider a view in front of you that is 90 degrees by 90 degrees, like looking through an open window at a scene. The number of pixels would be:
90 degrees * 60 arc-minutes/degree * 1/0.3 * 90 * 60 * 1/0.3 = 324,000,000 pixels (324 megapixels).
At any one moment, you actually do not perceive that many pixels, but your eye moves around the scene to see all the detail you want. But the human eye really sees a larger field of view, close to 180 degrees. Let’s be conservative and use 120 degrees for the field of view. Then we would see:
Shutter is the device that controls the amount of light through a lens. Basically in general it controls the amount of time a film is exposed.
Shutter speed is how long this device is open for, which also defines motion blur… the longer it stays open the blurrier the image captured.
The number refers to the amount of light actually allowed through.
As a reference, shooting at 24fps, at 180 shutter angle or 1/48th of shutter speed (0.0208 exposure time) will produce motion blur which is similar to what we perceive at naked eye
Talked of as in (shutter) angles, for historical reasons, as the original exposure mechanism was controlled through a pie shaped mirror in front of the lens.
A shutter of 180 degrees is blocking/allowing light for half circle. (half blocked, half open). 270 degrees is one quarter pie shaped, which would allow for a higher exposure time (3 quarter pie open, vs one quarter closed) 90 degrees is three quarter pie shaped, which would allow for a lower exposure (one quarter open, three quarters closed)
For example here is a chart from shutter angle to shutter speed at 24 fps: 270 = 1/32
180 = 1/48
172.8 = 1/50
144 = 1/60
90 = 1/96
72 = 1/120
45 = 1/198
22.5 = 1/348
11 = 1/696
8.6 = 1/1000
The above is basically the relation between the way a video camera calculates shutter (fractions of a second) and the way a film camera calculates shutter (in degrees).
Smaller shutter angles show strobing artifacts. As the camera only ever sees at least half of the time (for a typical 180 degree shutter). Due to being obscured by the shutter during that period, it doesn’t capture the scene continuously.
This means that fast moving objects, and especially objects moving across the frame, will exhibit jerky movement. This is called strobing. The defect is also very noticeable during pans. Smaller shutter angles (shorter exposure) exhibit more pronounced strobing effects.
Larger shutter angles show more motion blur. As the longer exposure captures more motion.
Note that in 3D you want to first sum the total of the shutter open and shutter close values, than compare that to the shutter angle aperture, ie:
shutter open -0.0625
shutter close 0.0625
Total shutter = 0.0625+0.0625 = 0.125
Shutter angle = 360*0.125 = 45
shutter open -0.125
shutter close 0.125
Total shutter = 0.125+0.125 = 0.25
Shutter angle = 360*0.25 = 90
shutter open -0.25
shutter close 0.25
Total shutter = 0.25+0.25 = 0.5
Shutter angle = 360*0.5 = 180
shutter open -0.375
shutter close 0.375
Total shutter = 0.375+0.375 = 0.75
Shutter angle = 360*0.75 = 270
