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Qwen Image Edit w/ Camera Control is wild 🤯 Quickly rotate the camera, switch between bird's eye and worm's eye views using just clicks. Here's how plus 7 wild examples:👇

Min Choi

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309,313 次观看 • 9 个月前 •via X (Twitter)

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adding camera control to the list of things Qwen Image Edit is great at + with a specialized multi-angle LoRA it's even better✨ > rotate the camera > tilt between bird’s-eye and worm’s-eye views > adjust lens (wide, close-up) of course we built a demo for it 🤝📹

adding camera control to the list of things Qwen Image Edit is great at + with a specialized multi-angle LoRA it's even better✨ > rotate the camera > tilt between bird’s-eye and worm’s-eye views > adjust lens (wide, close-up) of course we built a demo for it 🤝📹

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Camera angle editing has never been this intuitive & fast 🔥 Just added apolinario (poli) 's 3D interactive component to the Qwen Camera Angle Control demo, using 大雄's Qwen-Edit-2509-Multiple-Angles LoRA Simply drag the camera around 👇

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By far the best way to generate images at different angles is this 3D Camera Control node. Instead of describing angles with words, you just click the view you want. Simple UI, and the Qwen Image Edit 2511 multi-angle LoRA keeps things consistent across generations. Workflow below 👇

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I’ve just finished watching Apple’s visionOS sessions. Some of these concepts and the way Apple has implemented the design is mind blowing 🤯 Here are 5 examples that I loved: 1. Eye zoom. Just look at _where_ on an image you want to zoom in, and pinch your fingers apart

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Impossible Nature. My goal here was to generate images with a low quality aesthetic that are slightly overexposed and then apply handheld camera motion to it with focal shifts, quick zoom in/out + tracking. I just wanted to see how far I could push realism from an alternate universe. Nano Banana Pro let's you construct animals out of practically anything, it's wild. What do you think? Does it look believable? Images generated with Google's Nano Banana Pro. Image to video using Kling AI 2.5 1 - A crab made entirely out of seashells captured on the beach at night.

Impossible Nature. My goal here was to generate images with a low quality aesthetic that are slightly overexposed and then apply handheld camera motion to it with focal shifts, quick zoom in/out + tracking. I just wanted to see how far I could push realism from an alternate universe. Nano Banana Pro let's you construct animals out of practically anything, it's wild. What do you think? Does it look believable? Images generated with Google's Nano Banana Pro. Image to video using Kling AI 2.5 1 - A crab made entirely out of seashells captured on the beach at night.

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Every click preserves a moment that can never be repeated Generated with BudgetPixel AI Prompt 👇 A professional female wildlife photographer in a dense jungle, shot in true-to-life documentary style, early morning golden hour with soft mist, natural lighting, highly realistic environment. She moves carefully and silently through foliage with a high-end DSLR and telephoto lens, wearing neutral outdoor gear. Subtle handheld camera movement for realism.* She suddenly spots a Bengal tiger resting with two cubs in the wild. The scene feels authentic and undisturbed. She slowly crouches, stabilizes her camera, adjusts focus and aperture — extreme close-up of her finger pressing the shutter, capturing the moment. Cut to ultra-realistic telephoto shots: the tiger calmly watching, cubs playfully moving around, detailed fur, natural eye movement, dust particles in the air. No exaggeration — pure documentary realism. Include professional camera work: over-the-shoulder shot, tight lens framing, shallow depth of field, natural focus pulls, slight lens breathing. Add subtle slow-motion (only for key moments like cub movement and tiger head turn), maintaining realism.* Ambient audio: real jungle sounds — birds, insects, leaves rustling, distant animal calls, camera shutter clicks. No artificial effects. Ending: she quietly exhales in awe, small genuine smile, reviews the captured shots on camera screen. No dramatic acting — natural human reaction. Ultra-realistic, 4K, HDR, National Geographic/BBC Earth style, cinematic but grounded in reality.

Every click preserves a moment that can never be repeated Generated with BudgetPixel AI Prompt 👇 A professional female wildlife photographer in a dense jungle, shot in true-to-life documentary style, early morning golden hour with soft mist, natural lighting, highly realistic environment. She moves carefully and silently through foliage with a high-end DSLR and telephoto lens, wearing neutral outdoor gear. Subtle handheld camera movement for realism.* She suddenly spots a Bengal tiger resting with two cubs in the wild. The scene feels authentic and undisturbed. She slowly crouches, stabilizes her camera, adjusts focus and aperture — extreme close-up of her finger pressing the shutter, capturing the moment. Cut to ultra-realistic telephoto shots: the tiger calmly watching, cubs playfully moving around, detailed fur, natural eye movement, dust particles in the air. No exaggeration — pure documentary realism. Include professional camera work: over-the-shoulder shot, tight lens framing, shallow depth of field, natural focus pulls, slight lens breathing. Add subtle slow-motion (only for key moments like cub movement and tiger head turn), maintaining realism.* Ambient audio: real jungle sounds — birds, insects, leaves rustling, distant animal calls, camera shutter clicks. No artificial effects. Ending: she quietly exhales in awe, small genuine smile, reviews the captured shots on camera screen. No dramatic acting — natural human reaction. Ultra-realistic, 4K, HDR, National Geographic/BBC Earth style, cinematic but grounded in reality.

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Multi-person chaos + high-frequency camera shake = the ultimate death trap for AI video. But look at this. 🤯 BytePlus Seedance 2.0 - 4K just mastered the chaotic "fan-cam" look in native 4K. Even with dozens of fans jumping, hugging, and screaming in a wild crowd: - Hair strands stay individual and razor-sharp. - Jersey and scarf textures don’t blur into mush. - Human anatomy remains 100% intact through the movement. This isn’t just video generation. This is uncompromised motion clarity. BytePlus Lumina Enterprises and Developers can access the official API via BytePlus, and you can also use it directly on BytePlus Lumina.

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🔥 VIDU Multi-Entity Consistency Give Vidu 2/3 images and it’ll turn them into a video—it’s pure magic! ✨ Your own characters interacting with objects and in the exact environment you want! Ads, movies… endless possibilities, and this is just the beginning! Thanks @Viduforhuman The future is a carrot! 🥕 Plus, how about grabbing any frame from a Vidu-generated video "from scratch" and throwing it into another AI video or image tool to push your project even further? For now, check out the comment below: I scaled up a frame with Magnific.ai and fed it into Runway to create a dynamic shot using full camera control. But fingers crossed I can soon use #ReCapture by Bisho & team to generate new shots from the same video!

🔥 VIDU Multi-Entity Consistency Give Vidu 2/3 images and it’ll turn them into a video—it’s pure magic! ✨ Your own characters interacting with objects and in the exact environment you want! Ads, movies… endless possibilities, and this is just the beginning! Thanks @Viduforhuman The future is a carrot! 🥕 Plus, how about grabbing any frame from a Vidu-generated video "from scratch" and throwing it into another AI video or image tool to push your project even further? For now, check out the comment below: I scaled up a frame with Magnific.ai and fed it into Runway to create a dynamic shot using full camera control. But fingers crossed I can soon use #ReCapture by Bisho & team to generate new shots from the same video!

Hungry Donkey 🥕

37,561 次观看 • 1 年前

📖THE STEP MOST CREATORS SKIP IS WHY THEIR AI ANIMATION LOOKS INCONSISTENT Consistency across clips doesn't come from prompting — it comes from the reference image. The pipeline, step by step: ▪ Start with ChatGPT Image 2 — generate a full character design sheet first, not just a single frame. Multiple angles, expressions, and outfit variations in one image keeps the character consistent across every scene ▪ Build a storyboard inside ChatGPT Image 2 as well — define each shot, camera angle, action, and mood before touching Seedance at all. This is the step most people skip and it's the reason clips look disconnected ▪ Define a color palette and lighting mood early — golden afternoon light, soft warm tones, dramatic shadows. Lock those values and repeat them across every prompt ▪ Take each storyboard frame into Seedance 2.0 as the reference image — one frame becomes one clip ▪ Write the Seedance prompt around the character action, not the scene description. The scene is already in the image. The prompt handles motion, camera behavior, and timing ▪ Keep clip duration between 4-6 seconds per shot — shorter clips give more control over pacing and reduce motion drift on character faces ▪ Match camera movement type across consecutive clips — if one shot dollies in, the next should hold or pull back, not dolly again The consistency across these frames comes from the character design sheet, not from luck. Seedance reads the reference image and the prompt together — if the reference is detailed enough, the output stays on-model. This video was created by ALOKXMEHTA 📥 tomorrow: the exact ChatGPT Image 2 prompt structure used to generate a multi-angle character design sheet like this one 🔖One article covers the entire workflow — it is pinned below, do not scroll past it.

📖THE STEP MOST CREATORS SKIP IS WHY THEIR AI ANIMATION LOOKS INCONSISTENT Consistency across clips doesn't come from prompting — it comes from the reference image. The pipeline, step by step: ▪ Start with ChatGPT Image 2 — generate a full character design sheet first, not just a single frame. Multiple angles, expressions, and outfit variations in one image keeps the character consistent across every scene ▪ Build a storyboard inside ChatGPT Image 2 as well — define each shot, camera angle, action, and mood before touching Seedance at all. This is the step most people skip and it's the reason clips look disconnected ▪ Define a color palette and lighting mood early — golden afternoon light, soft warm tones, dramatic shadows. Lock those values and repeat them across every prompt ▪ Take each storyboard frame into Seedance 2.0 as the reference image — one frame becomes one clip ▪ Write the Seedance prompt around the character action, not the scene description. The scene is already in the image. The prompt handles motion, camera behavior, and timing ▪ Keep clip duration between 4-6 seconds per shot — shorter clips give more control over pacing and reduce motion drift on character faces ▪ Match camera movement type across consecutive clips — if one shot dollies in, the next should hold or pull back, not dolly again The consistency across these frames comes from the character design sheet, not from luck. Seedance reads the reference image and the prompt together — if the reference is detailed enough, the output stays on-model. This video was created by ALOKXMEHTA 📥 tomorrow: the exact ChatGPT Image 2 prompt structure used to generate a multi-angle character design sheet like this one 🔖One article covers the entire workflow — it is pinned below, do not scroll past it.

Zentrix⌚️

12,846 次观看 • 1 个月前