FlashVSR is a streaming, one-step diffusion-based video super-resolution framework with block-sparse attention and a Tiny Conditional Decoder. It reaches ~17 FPS at 768×1408 on a single A100 GPU. A Locality-Constrained Attention design further improves generalization and perceptual quality on ultra-high-resolution videos.
Stable Video Infinity (SVI) is able to generate ANY-length videos with high temporal consistency, plausible scene transitions, and controllable streaming storylines in ANY domains.
OpenSVI: Everything is open-sourced: training & evaluation scripts, datasets, and more.
Infinite Length: No inherent limit on video duration; generate arbitrarily long stories (see the 10‑minute “Tom and Jerry” demo).
Versatile: Supports diverse in-the-wild generation tasks: multi-scene short films, single‑scene animations, skeleton-/audio-conditioned generation, cartoons, and more.
Efficient: Only LoRA adapters are tuned, requiring very little training data: anyone can make their own SVI easily.
VISTA is a modular, configurable framework for optimizing text-to-video generation. Given a user video prompt P, it produces an optimized video V* and its refined prompt P* through two phases: (i) Initialization and (ii) Self-Improvement, inspired by the human video optimization process via prompting. During (i), the prompt is parsed and planned into variants to generate candidate videos (Step 1), after which the best video-prompt pair is selected (Step 2). In (ii), the system generates multi-dimensional, multi-agent critiques (Step 3), refines the prompt (Step 4), produces new videos, and reselects the champion pair (Step 2). This phase continues until a stopping criterion is met or the maximum number of iterations is reached.
We introduce a principle, Oz, for displaying color imagery: directly controlling the human eye’s photoreceptor activity via cell-by-cell light delivery. Theoretically, novel colors are possible through bypassing the constraints set by the cone spectral sensitivities and activating M cone cells exclusively. In practice, we confirm a partial expansion of colorspace toward that theoretical ideal. Attempting to activate M cones exclusively is shown to elicit a color beyond the natural human gamut, formally measured with color matching by human subjects. They describe the color as blue-green of unprecedented saturation. Further experiments show that subjects perceive Oz colors in image and video form. The prototype targets laser microdoses to thousands of spectrally classified cones under fixational eye motion. These results are proof-of-principle for programmable control over individual photoreceptors at population scale.
SeC (Segment Concept) is a breakthrough in video object segmentation that shifts from simple feature matching to high-level conceptual understanding. Unlike SAM 2.1 which relies primarily on visual similarity, SeC uses a Large Vision-Language Model (LVLM) to understand what an object is conceptually, enabling robust tracking through:
Semantic Understanding: Recognizes objects by concept, not just appearance
Scene Complexity Adaptation: Automatically balances semantic reasoning vs feature matching
Superior Robustness: Handles occlusions, appearance changes, and complex scenes better than SAM 2.1
SOTA Performance: +11.8 points over SAM 2.1 on SeCVOS benchmark
How SeC Works
Visual Grounding: You provide initial prompts (points/bbox/mask) on one frame
Concept Extraction: SeC’s LVLM analyzes the object to build a semantic understanding
Smart Tracking: Dynamically uses both semantic reasoning and visual features
Keyframe Bank: Maintains diverse views of the object for robust concept understanding
The result? SeC tracks objects more reliably through challenging scenarios like rapid appearance changes, occlusions, and complex multi-object scenes.
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)
To measure the contrast ratio you will need a light meter. The process starts with you measuring the main source of light, or the key light.
Get a reading from the brightest area on the face of your subject. Then, measure the area lit by the secondary light, or fill light. To make sense of what you have just measured you have to understand that the information you have just gathered is in F-stops, a measure of light. With each additional F-stop, for example going one stop from f/1.4 to f/2.0, you create a doubling of light. The reverse is also true; moving one stop from f/8.0 to f/5.6 results in a halving of the light.
In HD we often refer to the range of available colors as a color gamut. Such a color gamut is typically plotted on a two-dimensional diagram, called a CIE chart, as shown in at the top of this blog. Each color is characterized by its x/y coordinates.
Good enough for government work, perhaps. But for HDR, with its higher luminance levels and wider color, the gamut becomes three-dimensional.
For HDR the color gamut therefore becomes a characteristic we now call the color volume. It isn’t easy to show color volume on a two-dimensional medium like the printed page or a computer screen, but one method is shown below. As the luminance becomes higher, the picture eventually turns to white. As it becomes darker, it fades to black. The traditional color gamut shown on the CIE chart is simply a slice through this color volume at a selected luminance level, such as 50%.
Three different color volumes—we still refer to them as color gamuts though their third dimension is important—are currently the most significant. The first is BT.709 (sometimes referred to as Rec.709), the color gamut used for pre-UHD/HDR formats, including standard HD.
The largest is known as BT.2020; it encompasses (roughly) the range of colors visible to the human eye (though ET might find it insufficient!).
Between these two is the color gamut used in digital cinema, known as DCI-P3.
