Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Let this chocolate brown Countach heal your algorithm! This commercial started as nothing more than an idea. I wanted to create something that felt timeless a chocolate brown Lamborghini Countach, an old-money atmosphere, a powerful woman, a luxury mansion party, natural daylight, authentic human interactions, and a commercial so... realistic it wouldn't feel AI-generated at all. So I sat down with ChatGPT and explained the vision in detail. First, we built the story. I described the world, the mood, the characters, the setting, and the feeling I wanted viewers to experience. From there, ChatGPT helped transform that vision into a complete narrative, turning scattered ideas into a cinematic concept. Next came the planning stage. The story was broken down into a professional commercial timeline, scene by scene, shot by shot, exactly how a luxury automotive campaign would be storyboarded by a creative director and videographer. Then we went even deeper. Every scene was translated into detailed prompts, camera directions, movement instructions, lighting setups, slow-motion sequences, environmental details, character positioning, and luxury automotive close-ups. Once the sequence felt perfect, those ideas were converted into structured JSON prompts to maintain consistency throughout the project. After that, I generated individual storyboard images for every scene. Each image became a visual reference frame representing a specific moment of the commercial the mansion, the audience, the old-money styling, the Countach hero shots, the interior reveals, the scissor doors, and the final cinematic departure. Those reference images were then brought into Yapper where I used Seedance 2.0 to generate the actual video sequences. Multiple generations. Multiple revisions. Multiple refinements. Frame by frame, the vision started becoming reality. Finally, I edited both video sequences together, refined the pacing, synchronized the transitions, selected the music, and shaped everything into one seamless luxury automotive commercial. What you're watching isn't just an AI video. It's the result of storytelling, creative direction, prompt engineering, shot planning, storyboard creation, image generation, video generation, editing, and countless creative decisions. A chocolate brown Lamborghini Countach. An old-money lifestyle. A cinematic luxury fantasy brought to life from a single idea. Built through imagination. Designed through collaboration. Created frame by frame.show more

Julia Clark

7,450 subscribers

26,529 просмотров • 21 дней назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

What if a pair of heels became the hero of a cinematic chase scene? Made mine with the help of FlovaAI This entire luxury commercial started with a single product idea and a simple creative direction. Flova AI 1.0 handled the storyboard, shots, camera movements, and visual storytelling. For product commercials, you only need a product image and a one-line direction, it generates everything else for you. #FlovaAIChallenge

What if a pair of heels became the hero of a cinematic chase scene? Made mine with the help of FlovaAI This entire luxury commercial started with a single product idea and a simple creative direction. Flova AI 1.0 handled the storyboard, shots, camera movements, and visual storytelling. For product commercials, you only need a product image and a one-line direction, it generates everything else for you. #FlovaAIChallenge

Jessica Collins

31,148 просмотров • 16 дней назад

Co-produced with PAI by Utopai Studios, the first long-form video generation model. The AI video clip era is ending! I started with a short story idea. From there, PAI generated the characters, transformed them into keyframes, and then animated the scenes into a full sequence. The interesting part was seeing how the same characters, environment, and visual style stayed consistent across multiple shots while the story progressed naturally. What felt different here is that I wasn’t building each shot manually. I focused on the narrative, and the engine handled character creation, scene continuity, and animation to produce a ready-to-watch video. A step-by-step tutorial so you can make your own story 👇🏻 Thanks to Utopai Studios for collaborating with me Try it now: #UtopaiPartners

Co-produced with PAI by Utopai Studios, the first long-form video generation model. The AI video clip era is ending! I started with a short story idea. From there, PAI generated the characters, transformed them into keyframes, and then animated the scenes into a full sequence. The interesting part was seeing how the same characters, environment, and visual style stayed consistent across multiple shots while the story progressed naturally. What felt different here is that I wasn’t building each shot manually. I focused on the narrative, and the engine handled character creation, scene continuity, and animation to produce a ready-to-watch video. A step-by-step tutorial so you can make your own story 👇🏻 Thanks to Utopai Studios for collaborating with me Try it now: #UtopaiPartners

Amira Zairi

25,679 просмотров • 3 месяцев назад

Been playing with a character consistency workflow again. This came from Nexora that starts with a single GPT Image 2.0 character sheet and turns it into a multi-shot cinematic sequence in Seedance 2.0. One thing I added to the workflow: I first comped the character, environment, and visual style together in Midjourney before bringing everything into GPT Image 2.0 to build the character sheet. I also pushed it a bit further by generating multiple characters, destinations, and art directions at the same time, then turning those into production-style character sheets and shot sequences. It's interesting how much consistency you can get from a single well-defined character board when the visual language, wardrobe, and environment are established upfront. Check out three different character + scenes here 👇

Been playing with a character consistency workflow again. This came from Nexora that starts with a single GPT Image 2.0 character sheet and turns it into a multi-shot cinematic sequence in Seedance 2.0. One thing I added to the workflow: I first comped the character, environment, and visual style together in Midjourney before bringing everything into GPT Image 2.0 to build the character sheet. I also pushed it a bit further by generating multiple characters, destinations, and art directions at the same time, then turning those into production-style character sheets and shot sequences. It's interesting how much consistency you can get from a single well-defined character board when the visual language, wardrobe, and environment are established upfront. Check out three different character + scenes here 👇

Curious Refuge

12,209 просмотров • 15 дней назад

GPT Image 2 + Seedance 2 = an animated cinematic universe. I was curious about what boundaries exist for AI storytelling continuity, so I built the world of Donotopia, a Pixar-style universe, filled with comedy, emotional arcs, destruction, big boss fights and continuity of multiple scenes. I was surprised with how powerful the workflow was: - Inside GPT Image 2, I generated 3x3 storyboard sheets with 3x3 scenes for a total of 27 scenes. - Each scene was designed and drawn as a step of pre-production in animation. - Heaps of images were generated, resulting in a Character Kit for a Bobo Gigglesworth, with references for facial expression, baggy clothes and personality. - Shot continuity was maintained in the scene diagrams. - The angles of the shots were directed as actual film, including crane shots, low angle shots, chaos shots and cinematic push-ins. - The destruction was choreographed with emotional arcs and continuity of the environment. - Seedance 2 was used to transform the drawings of the film into animated storyboard shots. The story evolved way beyond what I expected:

GPT Image 2 + Seedance 2 = an animated cinematic universe. I was curious about what boundaries exist for AI storytelling continuity, so I built the world of Donotopia, a Pixar-style universe, filled with comedy, emotional arcs, destruction, big boss fights and continuity of multiple scenes. I was surprised with how powerful the workflow was: - Inside GPT Image 2, I generated 3x3 storyboard sheets with 3x3 scenes for a total of 27 scenes. - Each scene was designed and drawn as a step of pre-production in animation. - Heaps of images were generated, resulting in a Character Kit for a Bobo Gigglesworth, with references for facial expression, baggy clothes and personality. - Shot continuity was maintained in the scene diagrams. - The angles of the shots were directed as actual film, including crane shots, low angle shots, chaos shots and cinematic push-ins. - The destruction was choreographed with emotional arcs and continuity of the environment. - Seedance 2 was used to transform the drawings of the film into animated storyboard shots. The story evolved way beyond what I expected:

Beginnersblog

15,820 просмотров • 1 месяц назад

Bring your stories to life with a 3D camera. Start with a single frame and turn it into a 3D scene you can move through, shot by shot. Control the camera. Set the pace. Shape the story.

Bring your stories to life with a 3D camera. Start with a single frame and turn it into a 3D scene you can move through, shot by shot. Control the camera. Set the pace. Shape the story.

Moonvalley

18,713 просмотров • 10 месяцев назад

Just tested Runway Aleph 2.0 and this blew my mind a bit lol I saw a video like this when Aleph first released and with the new Aleph 2.0 I wanted to create my own version. You basically select a single frame from the video, apply a change to that specific frame using Nano Banana Pro, GPT Image 2 or Gen-4 and based on the newly generated image Aleph propagates the change through the entire shot. It's really cool seeing the whole sequence adapt from just one edited frame

Just tested Runway Aleph 2.0 and this blew my mind a bit lol I saw a video like this when Aleph first released and with the new Aleph 2.0 I wanted to create my own version. You basically select a single frame from the video, apply a change to that specific frame using Nano Banana Pro, GPT Image 2 or Gen-4 and based on the newly generated image Aleph propagates the change through the entire shot. It's really cool seeing the whole sequence adapt from just one edited frame

Ege

87,551 просмотров • 1 месяц назад

The power of this AI is honestly insane. A Naruto scene was transformed into live-action using a video reference and simple text prompt. The motion stays the same, but every frame gets a cinematic look – even during fast action.

The power of this AI is honestly insane. A Naruto scene was transformed into live-action using a video reference and simple text prompt. The motion stays the same, but every frame gets a cinematic look – even during fast action.

Aleena Amir

264,020 просмотров • 3 месяцев назад

The Legend of the Crowned Duck🦆👑 Pollo AI PolloAI Creators Three emojis. One dark sanctuary. An ancient crown. And a story that feels like it belongs in a forgotten myth. I challenged AI to create a cinematic legend using nothing more than 🦆 👑 🔥 What emerged was a hyper-realistic ruler standing in the shadows, surrounded by rising embers, ancient stone, and a kingdom on the edge of awakening. Every frame started as a simple idea. The result feels like a scene pulled from an epic fantasy film. Built entirely with AI. Workflow and Prompts below👇🏾 #PolloAI #PolloMeme

The Legend of the Crowned Duck🦆👑 Pollo AI PolloAI Creators Three emojis. One dark sanctuary. An ancient crown. And a story that feels like it belongs in a forgotten myth. I challenged AI to create a cinematic legend using nothing more than 🦆 👑 🔥 What emerged was a hyper-realistic ruler standing in the shadows, surrounded by rising embers, ancient stone, and a kingdom on the edge of awakening. Every frame started as a simple idea. The result feels like a scene pulled from an epic fantasy film. Built entirely with AI. Workflow and Prompts below👇🏾 #PolloAI #PolloMeme

Gilbert Odera | Your AI Plug🇰🇪

22,350 просмотров • 8 дней назад

So Runway Aleph 2.0 just dropped, and it introduces a pretty interesting workflow for AI video footage editing. Rather than repeatedly prompting a video model and hoping it makes the change you want, you can edit a specific frame first, then use that frame to guide the video generation. For this test, I take an existing footage inside Runway: • Picked a frame from the original video • Used Nano Banana Pro to add a new effect/object • Brought that frame into Aleph 2.0 to generate the updated video It feels like a more controllable and potentially cheaper way to make targeted edits to existing footage than current AI video omni models available like Seedance and Gemini.

So Runway Aleph 2.0 just dropped, and it introduces a pretty interesting workflow for AI video footage editing. Rather than repeatedly prompting a video model and hoping it makes the change you want, you can edit a specific frame first, then use that frame to guide the video generation. For this test, I take an existing footage inside Runway: • Picked a frame from the original video • Used Nano Banana Pro to add a new effect/object • Brought that frame into Aleph 2.0 to generate the updated video It feels like a more controllable and potentially cheaper way to make targeted edits to existing footage than current AI video omni models available like Seedance and Gemini.

Curious Refuge

11,144 просмотров • 14 дней назад

From Late-Night Match Chaos to Stadium Atmosphere⚽🔥 Pollo AI Every football fan knows the feeling. The final whistle blows. The snacks are gone. The room feels exhausted. So I imagined a product ad built around a simple question: What if one spray could transform an ordinary living room into the energy of a packed stadium? That idea became this cinematic AI-generated commercial. A simple product. A dramatic transformation. A story people instantly understand. Check my workflow and prompts below👇🏾 #PolloAI #PolloScore

From Late-Night Match Chaos to Stadium Atmosphere⚽🔥 Pollo AI Every football fan knows the feeling. The final whistle blows. The snacks are gone. The room feels exhausted. So I imagined a product ad built around a simple question: What if one spray could transform an ordinary living room into the energy of a packed stadium? That idea became this cinematic AI-generated commercial. A simple product. A dramatic transformation. A story people instantly understand. Check my workflow and prompts below👇🏾 #PolloAI #PolloScore

Gilbert Odera | Your AI Plug🇰🇪

37,397 просмотров • 21 дней назад

Our very own Alexander Chen created "Hello, world" a short film inspired by the technology of his childhood with Google Labs Flow. Here's a closer look at how he brought his vision to life: 1) All of the clips were generated in Flow using text-to-image prompts except he used image-to-video prompts for the close-up shots to ensure consistency and accuracy (and the images used were generated by Imagen). 2) To evoke the exact feelings of his childhood home, he used Google Street View for visual references then asked the Google Gemini to write descriptions and prompts, then uploaded those into Flow which is what produced such vivid and accurate renderings in the film. 3) Every sound used in the video is generated by Veo 3. However, to blend things together, he used a separate video editing software to extend the head and tail of each clip over the proceeding and following clip, occasionally crossfading the audio to help with transitions.

Our very own Alexander Chen created "Hello, world" a short film inspired by the technology of his childhood with Google Labs Flow. Here's a closer look at how he brought his vision to life: 1) All of the clips were generated in Flow using text-to-image prompts except he used image-to-video prompts for the close-up shots to ensure consistency and accuracy (and the images used were generated by Imagen). 2) To evoke the exact feelings of his childhood home, he used Google Street View for visual references then asked the Google Gemini to write descriptions and prompts, then uploaded those into Flow which is what produced such vivid and accurate renderings in the film. 3) Every sound used in the video is generated by Veo 3. However, to blend things together, he used a separate video editing software to extend the head and tail of each clip over the proceeding and following clip, occasionally crossfading the audio to help with transitions.

Google AI

94,790 просмотров • 1 год назад

i built a tool that lets you clone ANY video with AI saw a movie scene you want to recreate? a commercial? a music video? just upload it to this tool and get the exact structured prompt to generate it in sora 2 you no longer need to guess how to describe what you want to generate. show the tool the reference and it engineers the prompt for you. the tool analyzes: - camera movements and angles - lighting and color grading - scene composition and timing then converts everything into sora-optimized prompt structure this is how you recreate any visual style without prompt engineering experience RT + reply 'TOOL' and i'll send you access (must follow so i can dm)

i built a tool that lets you clone ANY video with AI saw a movie scene you want to recreate? a commercial? a music video? just upload it to this tool and get the exact structured prompt to generate it in sora 2 you no longer need to guess how to describe what you want to generate. show the tool the reference and it engineers the prompt for you. the tool analyzes: - camera movements and angles - lighting and color grading - scene composition and timing then converts everything into sora-optimized prompt structure this is how you recreate any visual style without prompt engineering experience RT + reply 'TOOL' and i'll send you access (must follow so i can dm)

Miko

42,842 просмотров • 8 месяцев назад

Two weeks in Japan. Hundreds of photos. One creative rabbit hole I couldn’t resist going down. Last year, I created a song as an experiment. I wanted to blend Japanese and English lyrics and see what kind of mood it would create. It turned into something atmospheric and different from anything I’d done before. Then my wife and I spent two incredible weeks in Japan late last year, and the experience stuck with me. Seeing the temples, shrines, and local shops while my wife and I wandered around Kyoto left a lasting impression. When I got back, I realized that the song needed a visual story. So I decided to build a full music video around it. I started by fleshing out the concept and writing a shot list like a real production. Then the fun began. What’s interesting is that many of the locations you see in the video actually started as photos I took while my wife and I wandered around Kyoto. Those images became the foundation for the environments that were later generated and brought to life with AI. It was a fascinating, creative process. Part music creation, part photography, part storytelling, and part AI experimentation. Tools used in the process: Nano Banana Pro (Google Flow) – for image generation Midjourney (Midjourney) – for additional image creation Google VEO3 (Google Flow) – for video generation Kling 3.0 (Kling AI) – for video generation Final Cut Pro (Apple) – for editing SUNO (Suno) – for song generation Amazing how far the creative toolset has come. If you have an idea in your head, you can now actually build it! Take a minute to watch Rain + Light (雨と光) and tell me what stood out to you. Would love to hear your feedback.

Two weeks in Japan. Hundreds of photos. One creative rabbit hole I couldn’t resist going down. Last year, I created a song as an experiment. I wanted to blend Japanese and English lyrics and see what kind of mood it would create. It turned into something atmospheric and different from anything I’d done before. Then my wife and I spent two incredible weeks in Japan late last year, and the experience stuck with me. Seeing the temples, shrines, and local shops while my wife and I wandered around Kyoto left a lasting impression. When I got back, I realized that the song needed a visual story. So I decided to build a full music video around it. I started by fleshing out the concept and writing a shot list like a real production. Then the fun began. What’s interesting is that many of the locations you see in the video actually started as photos I took while my wife and I wandered around Kyoto. Those images became the foundation for the environments that were later generated and brought to life with AI. It was a fascinating, creative process. Part music creation, part photography, part storytelling, and part AI experimentation. Tools used in the process: Nano Banana Pro (Google Flow) – for image generation Midjourney (Midjourney) – for additional image creation Google VEO3 (Google Flow) – for video generation Kling 3.0 (Kling AI) – for video generation Final Cut Pro (Apple) – for editing SUNO (Suno) – for song generation Amazing how far the creative toolset has come. If you have an idea in your head, you can now actually build it! Take a minute to watch Rain + Light (雨と光) and tell me what stood out to you. Would love to hear your feedback.

Chip – onthechain.io

12,993 просмотров • 3 месяцев назад

First frame + Last frame = Fashion ads in minutes. Here’s how I generated this U.S. Polo sequence using Kling 3.0 + Calico AI: → The Input: A start frame and an end frame to lock in the subject and composition. → The Prompt: Don't just ask for a "cool video." Specifically prompted for "slow cinematic push-in," "shallow depth of field," and "micro-parallax" to get that premium brand-film look. → The Output: Motion that looks like a high-budget fashion shoot. Studio shoots are expensive, but AI is leveling the playing field. Comment 'PROMPT' if you want me to send you all of the prompts and the system I used to build this. (must be following so I can dm you!)

David Roberts

25,878 просмотров • 4 месяцев назад

Workflow: Made this cinematic football short with a surprisingly simple workflow: - Created the character sheet in ChatGPT - Generated 3 connected storyboards (10 frames each) - Converted each storyboard into a detailed Seedance 2.0 video prompt - Generated all scenes in Seedance - Edited everything together into one film Character → Storyboards → Video Prompts → Seedance → Final Film.

Workflow: Made this cinematic football short with a surprisingly simple workflow: - Created the character sheet in ChatGPT - Generated 3 connected storyboards (10 frames each) - Converted each storyboard into a detailed Seedance 2.0 video prompt - Generated all scenes in Seedance - Edited everything together into one film Character → Storyboards → Video Prompts → Seedance → Final Film.

Beginnersblog

32,331 просмотров • 6 дней назад

Cinematic city transitions. Perfect cuts. Zero traditional video editing. Everything you’re watching is AI. Tools: - Kling 2.5 Turbo - Nano Banana Pro - ChatGPT 4 STEP TUTORIAL: 1️⃣: Design your concept Brainstorm with ChatGPT the type of “vibe” you want your images/video to capture. I landed on “Cinematic Urban Melancholy” for my overall Visual Theme. 2️⃣: Generate Images with Nano Banana 🍌 Use ChatGPT to generate nano-banana-ready prompts for each of the 5 images in your setting. 3️⃣: Generate AI Transitions Navigate to Kling and select AI Video Generator Upload your start frame (image 1) + end frame (image 2) Prompt for a “seamless cinematic transition between scenes”. You’ll need to iterate on your prompt until the result matches your vision. Be specific about motion, style, and mood. 4️⃣: Polish Import everything into your editor (I use CapCut). Add speed / slowdown. And most importantly, add sound design. Music and SFX sell the visuals. Bookmark this and try it out yourself! If you want the exact prompts I'm using to generate these transitions: Follow, RT, & comment 'PROMPTS' below. I'll dm them to you (must be following so i can message)

Cinematic city transitions. Perfect cuts. Zero traditional video editing. Everything you’re watching is AI. Tools: - Kling 2.5 Turbo - Nano Banana Pro - ChatGPT 4 STEP TUTORIAL: 1️⃣: Design your concept Brainstorm with ChatGPT the type of “vibe” you want your images/video to capture. I landed on “Cinematic Urban Melancholy” for my overall Visual Theme. 2️⃣: Generate Images with Nano Banana 🍌 Use ChatGPT to generate nano-banana-ready prompts for each of the 5 images in your setting. 3️⃣: Generate AI Transitions Navigate to Kling and select AI Video Generator Upload your start frame (image 1) + end frame (image 2) Prompt for a “seamless cinematic transition between scenes”. You’ll need to iterate on your prompt until the result matches your vision. Be specific about motion, style, and mood. 4️⃣: Polish Import everything into your editor (I use CapCut). Add speed / slowdown. And most importantly, add sound design. Music and SFX sell the visuals. Bookmark this and try it out yourself! If you want the exact prompts I'm using to generate these transitions: Follow, RT, & comment 'PROMPTS' below. I'll dm them to you (must be following so i can message)

David Roberts

230,135 просмотров • 5 месяцев назад

Fledgling After creating the character in Midjourney, generated the storyboard and video prompts. For the second video, used the first video as a reference and didn't include the second storyboard. Finally, I added the music. You can find the full workflow and prompts in the replies. Midjourney + GPT Image 2 + Seedance 2.0

Fledgling After creating the character in Midjourney, generated the storyboard and video prompts. For the second video, used the first video as a reference and didn't include the second storyboard. Finally, I added the music. You can find the full workflow and prompts in the replies. Midjourney + GPT Image 2 + Seedance 2.0

Kōda

15,735 просмотров • 9 дней назад

This GPT Image 2 prompt creates cinematic storyboard grids from your reference images while generating an original continuous sequence. You can see two different examples in the attached video. If you want a director-inspired cinematic tone, first use the separate “director language” prompt with a director name. It gives you abstract cinematic qualities without directly replicating copyrighted styles. If you don’t want that, you can simply remove that paragraph from the grid prompt. Then you can use the Seedance 2.0 prompt I shared to animate the storyboard grid into a cinematic sequence. You can find the prompts below.

This GPT Image 2 prompt creates cinematic storyboard grids from your reference images while generating an original continuous sequence. You can see two different examples in the attached video. If you want a director-inspired cinematic tone, first use the separate “director language” prompt with a director name. It gives you abstract cinematic qualities without directly replicating copyrighted styles. If you don’t want that, you can simply remove that paragraph from the grid prompt. Then you can use the Seedance 2.0 prompt I shared to animate the storyboard grid into a cinematic sequence. You can find the prompts below.

Kōda

10,616 просмотров • 1 месяц назад

Seedance 2.0 is allowing us to enter a new era of music video creation. Here is how I created HONEY. It was a quick test to see how well this workflow holds up. 🐝 1 - Write your song and generate the music with Suno 5.5. 2 - Use an image generator of your choice. For HONEY I combined both Grok Imagine for aesthetics and Nano Banana Pro for refined editing. 3 - In Capcut I import my audio and just save out a blank video video containing the audio. This step is important because this video file containing audio will now be used with Seedance 2.0 as a video reference with Omni. This allows the AI to apply automatic and realistic lipsync and movement to the music, it's extremely powerful! 4 - Once I have a both my image and video with audio as reference, I use Seedance 2.0 Omni and upload my starting image and then the video reference with the audio. 5 - From here I'm simply prompting like normal, specifying what's happening in my scene with detailed instructions, mentioning multi shots and camera angle changes and then specifying that the person is singing along to the song. I type out the lyrics that are present to have better lipsync accuracy. 6 - Once I have generated a video and like the result, I do video to video, so i upload that video that just got generated and type "The scene continues" and prompt new actions to take place. This allows you to expand on a narrative. These new shots can be used as B-ROLL and since I uploaded my video as reference I have full consistency of everything it saw in the video. This is also extremely powerful. 7 - This is actually the most difficult part. Edit in Capcut. This is where you need to understand pacing and shot selection from all the scenes you generated to bring it all together. You must be strategic with the editing. Goodluck! I'll probably record a video tutorial at some point as it's easier to see what is being done.

Seedance 2.0 is allowing us to enter a new era of music video creation. Here is how I created HONEY. It was a quick test to see how well this workflow holds up. 🐝 1 - Write your song and generate the music with Suno 5.5. 2 - Use an image generator of your choice. For HONEY I combined both Grok Imagine for aesthetics and Nano Banana Pro for refined editing. 3 - In Capcut I import my audio and just save out a blank video video containing the audio. This step is important because this video file containing audio will now be used with Seedance 2.0 as a video reference with Omni. This allows the AI to apply automatic and realistic lipsync and movement to the music, it's extremely powerful! 4 - Once I have a both my image and video with audio as reference, I use Seedance 2.0 Omni and upload my starting image and then the video reference with the audio. 5 - From here I'm simply prompting like normal, specifying what's happening in my scene with detailed instructions, mentioning multi shots and camera angle changes and then specifying that the person is singing along to the song. I type out the lyrics that are present to have better lipsync accuracy. 6 - Once I have generated a video and like the result, I do video to video, so i upload that video that just got generated and type "The scene continues" and prompt new actions to take place. This allows you to expand on a narrative. These new shots can be used as B-ROLL and since I uploaded my video as reference I have full consistency of everything it saw in the video. This is also extremely powerful. 7 - This is actually the most difficult part. Edit in Capcut. This is where you need to understand pacing and shot selection from all the scenes you generated to bring it all together. You must be strategic with the editing. Goodluck! I'll probably record a video tutorial at some point as it's easier to see what is being done.

Travis Davids

18,967 просмотров • 2 месяцев назад

DŌKYŌ: A Three-Minute-Long Single-Take Short Film Made with AI We can agree that Bytedance Seedance 2.0 totally changed how people create videos. Omni mode enabled faster creation of short films, solo creators making feature-length films, and you can create a 15-second commercial in one shot with a single prompt. But it also opened the door to long, continuous takes, which were not possible. Usually the length of a generated clip is limited to 8–15 seconds. Of course some people tried to cheat around this limitation by doing last frame first frame generation and stitching, but it breaks the camera movement and the pace of the actions. With Seedance, it was very different: instead of fighting the engine I was able to think about what I would like to see, instead of what are the limitations. I planned the framing, the camera movement, the action, and built the three-minute sequence step by step. Of course, this means if you later realize that something is wrong three or four sections earlier, you have to redo everything that follows. Visually, I wanted to maintain a very cinematic, low contrast, grainy, soft look, siilar to an expired 8mm or 16mm film, so there was no upscaling, rather the opposite: softening the image in every possible way. #DreaminaCPP Dreamina AI

DŌKYŌ: A Three-Minute-Long Single-Take Short Film Made with AI We can agree that Bytedance Seedance 2.0 totally changed how people create videos. Omni mode enabled faster creation of short films, solo creators making feature-length films, and you can create a 15-second commercial in one shot with a single prompt. But it also opened the door to long, continuous takes, which were not possible. Usually the length of a generated clip is limited to 8–15 seconds. Of course some people tried to cheat around this limitation by doing last frame first frame generation and stitching, but it breaks the camera movement and the pace of the actions. With Seedance, it was very different: instead of fighting the engine I was able to think about what I would like to see, instead of what are the limitations. I planned the framing, the camera movement, the action, and built the three-minute sequence step by step. Of course, this means if you later realize that something is wrong three or four sections earlier, you have to redo everything that follows. Visually, I wanted to maintain a very cinematic, low contrast, grainy, soft look, siilar to an expired 8mm or 16mm film, so there was no upscaling, rather the opposite: softening the image in every possible way. #DreaminaCPP Dreamina AI

László Gaál

19,452 просмотров • 8 дней назад