Design
AI video tools come with their own vocabulary: text-to-video, image-to-video, prompt adherence, seed, temporal consistency, upscaling, interpolation, synthetic media. Some terms come from filmmaking. Some come from machine learning. Others are product labels that sound more technical than they need to be.
This AI video glossary explains the terms creators actually need when generating, reviewing, editing, and publishing AI videos. It is written for marketers, small business owners, YouTubers, freelancers, and creators who want better results without becoming video engineers.
The point is not to memorize every term. The point is to know which word helps you make a better creative decision.
AI video glossary: quick answer
An AI video glossary is a plain-English guide to the words used in AI video generation, prompting, camera direction, editing, reviewing, exporting, and responsible publishing.
The most important terms to understand first are text-to-video, image-to-video, video-to-video, prompt, negative prompt, reference image, AI video model, seed, prompt adherence, temporal consistency, camera movement, aspect ratio, resolution, frame rate, upscaling, interpolation, artifact, synthetic media, and deepfake.
The easiest way to understand AI video terminology is by workflow:
What you generate → how you prompt it → how the camera moves → how the model behaves → how you edit the result → how you publish it responsibly.
That structure is more useful than a pure A-to-Z list because creators do not work alphabetically. You start with an idea, generate a clip, review what failed, edit the best output, and publish it somewhere.
Start here: the 15 most important AI video terms
If you only learn a few terms, start with these. They show up in tool interfaces, tutorials, prompt examples, model updates, and client feedback.
How to use this AI video glossary
Use this glossary when you are trying to describe what you want, understand a tool setting, or explain what went wrong in an output.
For example, “the video looks weird” is hard to fix. “The product has poor temporal consistency and the label is hallucinating” is much easier to act on.
Google DeepMind’s Veo prompt guide recommends adding details such as subject, action, style, camera movement, composition, ambiance, and sound. OpenAI’s Sora 2 prompting guide separates technical settings like duration and resolution from creative prompt details such as subject, motion, lighting, and style. Runway’s text-to-video prompting guide also focuses on describing what appears in the frame and how elements move.
In plain English: better AI video prompts sound less like “make something cinematic” and more like clear creative direction.
70 AI video terms every creator should know
AI video generation terms
1. AI video generation
AI video generation means using artificial intelligence to create or transform video content. You might start with text, an image, a script, an existing video, or a mix of inputs. It is the umbrella term for most workflows in this glossary.
2. Text-to-video
Text-to-video means creating a video from a written prompt. You describe the subject, action, setting, camera, lighting, and style, and the model generates a video from that instruction.
Example: “Create a 10-second vertical video of a ceramic mug on a wooden desk, with soft morning light and gentle steam rising.”
3. Image-to-video
Image-to-video means turning a still image into a moving clip. The image gives the model a visual anchor, while the prompt tells it what should move. This is useful for products, characters, brand visuals, and social ads.
4. Video-to-video
Video-to-video means using an existing video as the input and asking AI to transform it. You might change the style, lighting, mood, background, or visual treatment while keeping the core motion.
5. Script-to-video
Script-to-video means generating a video from a written script instead of a single prompt. The tool may break the script into scenes, add visuals, narration, captions, music, or transitions.
6. AI video model
An AI video model is the system that generates the video. Examples include Sora, Veo, Runway models, Hailuo, Pixverse, Seedance, MiniMax, and others. Different models may perform better at realism, animation, stylized motion, camera control, or character consistency.
7. Multimodal input
Multimodal input means giving the AI more than one type of input. Examples include text plus image, text plus video, script plus voiceover, or product photo plus prompt. Multimodal workflows usually give you more control than text alone.
8. Reference image
A reference image is an image used to guide the look of the generated video. It can define product shape, character appearance, room style, lighting mood, clothing, or brand colors.
9. Reference video
A reference video is an existing clip used to guide motion, style, pacing, or camera behavior. Not every tool supports it, but the idea matters because AI video workflows are moving beyond single-prompt generation.
10. Generation
A generation is one output created by the AI. If you run the same prompt four times and receive four clips, those are four generations.
11. Render
Render means producing the final playable video from your settings, edits, and generated assets. In casual use, people mix up “generate” and “render.” More precisely, the AI generates content, and the system renders a finished file or preview.
12. Output
Output is the result the AI gives you: a generated clip, edited video, image, or audio. Judge the output by the job it needs to do, not only by whether it looks impressive at first glance.
AI video prompting terms
13. Prompt
A prompt is the instruction you give the AI. A strong AI video prompt usually includes subject, setting, action, camera angle, camera movement, lighting, style, duration, aspect ratio, and details to avoid.
14. Negative prompt
A negative prompt tells the AI what to avoid. It helps reduce common issues like distorted hands, fake text, floating objects, extra fingers, warped logos, and unrealistic shadows.
15. Subject
The subject is the main person, object, animal, product, or scene element in the video. If the subject is unclear, the model may focus on the wrong thing.
16. Scene
A scene is the environment or situation where the action happens. “A small home kitchen in the early morning” is more useful than “a kitchen” because it gives the model context.
17. Action
Action is what happens in the clip. AI video usually works better with one clear action than five competing actions.
18. Style
Style describes the visual feel of the video: realistic, documentary, cinematic, anime, claymation, product commercial, vintage film, handheld phone video, or clean studio ad. Style helps, but it should not replace concrete details.
19. Prompt adherence
Prompt adherence means how closely the model follows your instructions. If you ask for a red backpack on a school desk and receive a blue suitcase in a hallway, prompt adherence is weak.
20. Prompt engineering
Prompt engineering is the practice of writing better instructions for AI tools. For creators, it does not mean complicated language. It means being clear about subject, action, camera, lighting, timing, references, and constraints.
21. Prompt template
A prompt template is a reusable prompt structure.
Example: “Create a [duration] [style] video of [subject] doing [action] in [setting]. Use [camera angle], [camera movement], and [lighting]. Avoid [common problems].”
22. Shot
A shot is one continuous view from the camera. For better AI video results, think in shots instead of trying to generate an entire ad, explainer, or story in one prompt.
23. Shot list
A shot list is a planned list of the clips you need. For example: wide shot of storefront, close-up of product, hands preparing order, final logo screen.
24. Storyboard
A storyboard is a visual plan for a video, broken into scenes or frames. You do not need polished drawings. Rough notes are often enough.
25. Keyframe
A keyframe is an important frame that defines a visual state at a specific moment. In AI video tools, keyframes may guide how a scene starts, changes, or ends.
26. First frame
The first frame is the starting image of the video. If your tool allows first-frame control, it can help with product placement, composition, and character appearance.
27. Last frame
The last frame is the ending image of the video. First-frame and last-frame control can help when you need a clip to begin and end in specific states, such as a product reveal or loop.
28. Loop
A loop is a video that repeats smoothly without an obvious jump. Loops are useful for website hero videos, product animations, ambient clips, music visualizers, and social backgrounds.
29. Duration
Duration is the length of the generated video. Shorter clips are often easier to control. Longer clips may drift, especially with complex hands, faces, objects, or camera movements.
30. Aspect ratio
Aspect ratio is the shape of the video frame. Common examples include 16:9 for YouTube and websites, 9:16 for TikTok, Reels, Shorts, and Stories, 1:1 for square posts, and 4:5 for social feed ads.
31. Resolution
Resolution is the size of the video in pixels, such as 720p, 1080p, 4K, 1920×1080, or 1080×1920. Higher resolution can look sharper, but it does not fix broken motion or weak composition.
32. Frame rate
Frame rate is how many frames play per second. Common frame rates include 24 fps for a film-like feel, 30 fps for standard web and social video, and 60 fps for smoother motion.
Camera and motion terms
33. Close-up
A close-up frames the subject tightly. Use it for emotion, texture, product details, and small actions. It can also expose AI mistakes with hands, teeth, and text.
34. Medium shot
A medium shot shows the subject from a moderate distance. It is often safer for human actions because the model does not need to render tiny details too closely.
35. Wide shot
A wide shot shows more of the environment. It helps establish context but can make small details less controlled.
36. Establishing shot
An establishing shot introduces the setting, such as an exterior shot of a bakery at sunrise or a desk setup before a tutorial begins.
37. POV shot
A POV shot shows the scene from a person’s point of view. It works well for unboxing, tutorials, product demos, and social content.
38. Over-the-shoulder shot
An over-the-shoulder shot frames the scene from behind a person’s shoulder. Use it for workplace scenes, tutorials, conversations, and creative process videos.
39. Macro shot
A macro shot is an extreme close-up used for tiny details, such as water droplets on a skincare bottle or texture on fabric.
40. Camera angle
Camera angle describes where the camera is placed relative to the subject: eye-level, low angle, high angle, top-down, counter-height, or ground-level.
41. Camera movement
Camera movement describes how the camera moves during the shot: static, slow push-in, pan, tilt, tracking shot, handheld, orbit, or pull-back. Do not ask for “dynamic movement.” Say what the camera does.
42. Static shot
A static shot means the camera does not move. Use it when accuracy matters more than drama, especially for product videos and explainers.
43. Handheld
Handheld means the camera looks like it is held by a person. Subtle handheld movement can make AI video feel more documentary and less over-polished.
44. Pan
A pan is horizontal camera movement from side to side. It is useful for revealing a scene, following a subject, or showing a product lineup.
45. Tilt
A tilt is vertical camera movement up or down. It can reveal height, scale, packaging, architecture, or a full outfit.
46. Push-in
A push-in means the camera slowly moves closer to the subject. It is useful for product and brand videos because it creates focus without requiring complex action.
47. Pull-back
A pull-back means the camera moves away from the subject, often revealing the wider scene.
48. Tracking shot
A tracking shot follows a moving subject. It can look impressive, but it is harder for AI to maintain in crowded or fast-moving scenes.
49. Depth of field
Depth of field describes how much of the image is in focus. Shallow depth of field keeps the subject sharp and the background blurry. Deep depth of field keeps more of the image clear.
50. Bokeh
Bokeh is the soft blur in out-of-focus areas, often visible as round light spots. It is common in product, beauty, and cinematic prompts.
51. Rack focus
Rack focus means shifting focus from one subject to another, such as from a coffee cup in the foreground to a person in the background.
52. Motion blur
Motion blur is the blur that appears when objects or cameras move quickly. Natural motion blur can make video feel real, but too much can hide detail.
53. Slow motion
Slow motion means the action appears slower than real time. Use it selectively. Too much slow motion can make simple clips feel fake or overdramatic.
Model and output terms
54. Diffusion model
A diffusion model is a type of generative AI model that starts from noise and gradually shapes it into media. You do not need the math. The practical takeaway is that small changes to prompts or settings can produce different results.
55. Latent space
Latent space is the model’s hidden map of visual and motion possibilities. When you change prompts, styles, references, or seeds, you steer the model through that map.
56. Token
A token is a unit of text that an AI model reads. It can be a word, part of a word, punctuation mark, or another text unit. Clarity matters more than word count.
57. Inference
Inference is the process where the model uses your input to generate an output. When you click “generate,” the model runs inference.
58. Training data
Training data is the material used to train an AI model. Creators usually do not control it. What you can control is your prompt, references, settings, edits, and publishing choices.
59. Conditioning
Conditioning means guiding the model with extra information, such as a text prompt, reference image, first frame, pose guide, camera direction, audio cue, or style reference.
60. Seed
A seed is a value that influences the randomness of a generation. Using the same seed with the same prompt and settings may help create similar outputs, depending on the tool.
61. Variation
A variation is a new version based on a prompt, image, video, or previous output. Variations are useful because the first output is rarely the final one.
62. Iteration
Iteration means improving through repeated attempts: generate, review, adjust, generate again, edit the best result.
63. Prompt drift
Prompt drift happens when the output slowly moves away from your instruction. A product might start as one shape and end as another, or a character may change across the clip.
64. Temporal consistency
Temporal consistency means subjects, objects, lighting, and details stay stable across frames. Poor temporal consistency causes flicker, mutation, and identity changes.
65. Character consistency
Character consistency means the same person, character, mascot, or avatar keeps the same appearance across shots. It matters for storytelling, ads, and recurring brand characters.
66. Object permanence
Object permanence means objects continue to exist and behave consistently when moving, rotating, or being partially hidden. A coffee cup should not disappear when a hand passes in front of it.
67. Hallucination
Hallucination is when AI invents something that was not requested or is not true, such as fake logos, unreadable signs, invented product labels, or objects appearing from nowhere.
68. Artifact
An artifact is a visible mistake in generated media. Common AI video artifacts include warped hands, flickering faces, melting objects, fake text, broken reflections, duplicated people, and strange background movement.
69. Upscaling
Upscaling means increasing the resolution of a video after generation. It can improve sharpness, but it does not fully fix bad composition, broken motion, or poor prompt direction.
70. Frame interpolation
Frame interpolation means adding extra frames between existing frames to make motion smoother. It can help choppy clips but may create errors if the original motion is unstable.
Commonly confused AI video terms
Some AI video terms sound similar but mean different things. This section is useful when reviewing outputs or giving feedback.
AI video terms by goal
You do not need every term all the time. Use the words that match the job.
Editing, export, and trust terms worth knowing
The main glossary above focuses on the 70 terms creators need most. These extra terms often appear once you move from generation into editing and publishing.
Timeline is the editing area where clips, audio, captions, images, and effects are arranged over time.
Clip is a single piece of video. Multiple clips can be edited together into a longer video.
B-roll is supporting footage that adds context or covers edits. AI video is often useful for B-roll when you need visual support but do not have footage.
A-roll is the main footage, usually the speaker, interview, product demo, or central narrative.
Voiceover is narration added over the video. It works well when you need clarity and do not want to rely on generated characters speaking perfectly.
Captions are text versions of spoken audio. Captions help viewers understand the video without sound and can improve accessibility.
Codec compresses and decompresses video. Common codecs include H.264, H.265/HEVC, VP9, and AV1.
Container format is the file wrapper that holds video, audio, subtitles, and metadata. Common examples include MP4, MOV, and WebM.
Watermark is a visible mark placed on a video, often showing a platform logo, creator mark, or ownership label.
Synthetic media is media created or significantly altered by AI. AI-generated videos, AI voices, AI avatars, and AI-edited footage can all be synthetic media.
Deepfake is AI-generated or AI-manipulated media that makes a real person appear to say or do something they did not say or do.
Consent means getting permission before using a person’s face, voice, identity, or private material.
Disclosure means telling viewers when content is AI-generated or AI-altered, especially when the context could mislead them.
Provenance means the origin and history of a piece of media: who created it, whether it was AI-generated, whether it was edited, and what source assets were used.
The Coalition for Content Provenance and Authenticity, or C2PA, develops open technical standards for media provenance and authenticity. For creators and brands, the practical lesson is simple: as synthetic media becomes more realistic, transparency becomes part of quality.
How these terms fit into a real AI video workflow
Say you want to create a short product video for a skincare bottle.
First, choose the workflow:
Image-to-video, because product accuracy matters.
Then write the prompt:
Create an 8-second realistic product video of this skincare bottle standing on a bathroom counter. Use a slow push-in, soft morning window light, shallow depth of field, and subtle reflections. Keep the bottle shape, label area, color, and cap unchanged. Avoid fake text, warped edges, extra bottles, floating shadows, and glossy plastic texture.
Then review the output using the right terms.
That is why terminology matters. It lets you describe what worked, what failed, and what to fix next.
Where Renderforest fits in the workflow
Most creators do not want to manage five separate tools just to make one video. They want to write the idea, generate visuals, adjust the result, add audio or captions, and export something usable.
Renderforest’s AI Video Generator lets creators work with several AI video models in one place, including Google Veo, OpenAI Sora, Minimax Hailuo, Pixverse, and ByteDance Seed, according to its product page. That makes it useful for testing different generation styles, comparing outputs, and turning raw AI clips into finished videos with scenes, music, voiceover, captions, and branding.
A simple workflow could look like this:
- Choose text-to-video, image-to-video, or script-to-video.
- Write a prompt using clear subject, action, camera, lighting, and style terms.
- Generate a few variations.
- Review the output for artifacts, consistency, and platform fit.
- Edit the strongest clip into a finished video.
- Export in the right format and aspect ratio.
The glossary terms above help you make better choices at each step.
FAQ
What is AI video generation?
AI video generation is the process of using artificial intelligence to create or transform video content from text, images, scripts, existing videos, or other inputs.
What is text-to-video?
Text-to-video is an AI workflow where you write a prompt and the model generates a video from that description.
What is image-to-video?
Image-to-video is an AI workflow where a still image becomes the visual reference for a moving video. It is useful for products, characters, interiors, and brand visuals.
What is a prompt in AI video?
A prompt is the instruction you give the AI. A strong AI video prompt usually includes the subject, setting, action, camera angle, camera movement, lighting, style, duration, and details to avoid.
What is a negative prompt?
A negative prompt tells the AI what not to include. For example, you might ask it to avoid warped hands, fake text, extra fingers, distorted logos, or floating objects.
What does prompt adherence mean?
Prompt adherence means how closely the AI follows your instructions. Strong prompt adherence means the output matches the subject, action, style, and constraints you requested.
What is temporal consistency?
Temporal consistency means that people, objects, lighting, and details stay stable across video frames. Poor temporal consistency causes flicker, mutations, and changing objects.
What is an AI video artifact?
An artifact is a visible mistake in AI-generated video, such as warped hands, flickering faces, melting objects, broken text, strange shadows, or duplicated background people.
What is upscaling?
Upscaling increases the resolution of a video after generation. It can make video sharper, but it does not fully fix bad motion, poor composition, or distorted objects.
What is synthetic media?
Synthetic media is media created or significantly altered by AI. AI-generated videos, voices, avatars, and edited footage can all be synthetic media.
Final takeaway
AI video terminology looks intimidating until you connect each term to the work it helps you do.
Some terms help you generate the clip: text-to-video, image-to-video, prompt, negative prompt, model, reference image. Some help you direct the scene: subject, action, camera movement, lighting, aspect ratio. Some help you judge the result: temporal consistency, prompt adherence, artifact, hallucination. Others help you finish and publish responsibly: upscaling, captions, codec, synthetic media, consent, disclosure.
You do not need to memorize every term. You need enough vocabulary to explain what you want, spot what went wrong, and improve the next version.
