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أرفعي صورة الدرس .. وأنسخي :prompt: Transform the attached reference image into a cinematic 3D video in the style of a Pop-up Book, while preserving all the key elements and details of the original image with high accuracy. Do not alter the identity of the people, buildings, products, colors,... or the overall composition of the scene. Make the image look as if it were a page inside a luxurious, handcrafted 3D book made from high-quality cardstock. The scene begins with the book closed or the page lying flat. Then, the page slowly opens, and the elements within the image gradually pop out from the page as layered three-dimensional paper structures, creating the realistic illusion of a physical Pop-up Book.show more

عبير الحسن

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MiniMax H3 Instead of sharing the prompts for each of these videos, I thought it would be more useful to share how I created that prompts. All of the videos were generated with text-to-video. First, find an image with the kind of scene, composition and mood you want to recreate. I used a few YouTube playlist thumbnails as references but Pinterest is also a great place to find inspiration. You can even use your own old or nostalgic photographs. Then upload the image to ChatGPT and ask it to describe the scene. The description it gives you can essentially become your text-to-video prompt. From there, you can generate completely new scenes with a similar composition, atmosphere and cinematic language. You can of course use the reference image directly with image-to-video or as a first frame. But if the original image isn't yours, I prefer using it only as visual inspiration and recreating the scene through text-to-video. This is the prompt I use with ChatGPT: "Describe the scene in this image in English, focusing primarily on what is happening, the characters, their actions and body language, the setting and the overall atmosphere. Also briefly describe the composition, framing, camera angle, approximate lens choice, lighting, color palette and cinematic aesthetic. Keep it concise and scene-focused rather than overly technical."

MiniMax H3 Instead of sharing the prompts for each of these videos, I thought it would be more useful to share how I created that prompts. All of the videos were generated with text-to-video. First, find an image with the kind of scene, composition and mood you want to recreate. I used a few YouTube playlist thumbnails as references but Pinterest is also a great place to find inspiration. You can even use your own old or nostalgic photographs. Then upload the image to ChatGPT and ask it to describe the scene. The description it gives you can essentially become your text-to-video prompt. From there, you can generate completely new scenes with a similar composition, atmosphere and cinematic language. You can of course use the reference image directly with image-to-video or as a first frame. But if the original image isn't yours, I prefer using it only as visual inspiration and recreating the scene through text-to-video. This is the prompt I use with ChatGPT: "Describe the scene in this image in English, focusing primarily on what is happening, the characters, their actions and body language, the setting and the overall atmosphere. Also briefly describe the composition, framing, camera angle, approximate lens choice, lighting, color palette and cinematic aesthetic. Keep it concise and scene-focused rather than overly technical."

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The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

AK

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What did you do to my friend !! 😡 This is the trending “Fight Prompt” going viral Prompt : Use the first uploaded image as the main reference for the school uniform, body proportions, pose, posture, background, camera angle, framing, and overall composition. Use the second uploaded image as the identity reference for the face and hairstyle. Create a realistic Korean influencer-style school uniform portrait where the person from the second image naturally appears wearing the school uniform from the first image, photographed in the same studio setting. Important: Keep the school uniform, blazer, shirt, tie, skirt or pants, and overall outfit design from the first image. Keep the body proportions, standing pose, hand placement, posture, camera angle, framing, and studio background from the first image. Replace the face with the person from the second image. Also preserve the hairstyle from the second image, including bangs, hairline, hair part, hair length, hair framing around the face, and overall hair silhouette. Do not use the hairstyle from the first image if it differs from the second image. Identity: The face from the second image must remain clearly recognizable. Preserve the second person’s face shape, eyes, nose, lips, skin tone, jawline, and overall facial impression. Do not turn the face into a generic attractive face. Do not beautify too heavily. Preserve the person’s recognizable identity, but do not copy the face too rigidly. Reinterpret it naturally so it looks like a realistic photo of the same person in this new school-uniform scene. Keep the same overall facial impression and identity while allowing natural refinement and seamless adaptation to the lighting, angle, and mood of the target image. Hair: Follow the hairstyle from the second image. Preserve the second person’s bangs, hairline, hair part, hair texture, hair length, and overall hairstyle impression. Only adapt the hair naturally so it fits the pose, lighting, and composition of the first image. Korean influencer mood: clean modern Korean influencer portrait polished but natural beauty soft photogenic expression subtle editorial mood stylish, slightly chic, youthful, and confident atmosphere refined but believable skin texture clear eyes with soft catchlights naturally pretty, not over-retouched avoid stiff ID-photo mood Lighting: soft Korean beauty lighting gentle facial brightness clean skin tone soft natural highlights on the face natural shadow transition subtle glow, but realistic skin texture avoid harsh flash avoid flat passport-photo lighting avoid dramatic studio glamour lighting Style: realistic photography clean studio portrait quality Korean influencer-style school portrait mood natural skin texture high detail seamless face and hair integration polished but believable Negative prompt: no identity loss no generic attractive face no over-beautified face no first-image hairstyle if different no awkward face blending no mismatched skin tone no mismatched hairline no distorted facial features no blurry eyes no deformed hands no extra fingers no change to the school uniform no change to the body pose no change to the background no cartoon style no anime style no text no watermark

What did you do to my friend !! 😡 This is the trending “Fight Prompt” going viral Prompt : Use the first uploaded image as the main reference for the school uniform, body proportions, pose, posture, background, camera angle, framing, and overall composition. Use the second uploaded image as the identity reference for the face and hairstyle. Create a realistic Korean influencer-style school uniform portrait where the person from the second image naturally appears wearing the school uniform from the first image, photographed in the same studio setting. Important: Keep the school uniform, blazer, shirt, tie, skirt or pants, and overall outfit design from the first image. Keep the body proportions, standing pose, hand placement, posture, camera angle, framing, and studio background from the first image. Replace the face with the person from the second image. Also preserve the hairstyle from the second image, including bangs, hairline, hair part, hair length, hair framing around the face, and overall hair silhouette. Do not use the hairstyle from the first image if it differs from the second image. Identity: The face from the second image must remain clearly recognizable. Preserve the second person’s face shape, eyes, nose, lips, skin tone, jawline, and overall facial impression. Do not turn the face into a generic attractive face. Do not beautify too heavily. Preserve the person’s recognizable identity, but do not copy the face too rigidly. Reinterpret it naturally so it looks like a realistic photo of the same person in this new school-uniform scene. Keep the same overall facial impression and identity while allowing natural refinement and seamless adaptation to the lighting, angle, and mood of the target image. Hair: Follow the hairstyle from the second image. Preserve the second person’s bangs, hairline, hair part, hair texture, hair length, and overall hairstyle impression. Only adapt the hair naturally so it fits the pose, lighting, and composition of the first image. Korean influencer mood: clean modern Korean influencer portrait polished but natural beauty soft photogenic expression subtle editorial mood stylish, slightly chic, youthful, and confident atmosphere refined but believable skin texture clear eyes with soft catchlights naturally pretty, not over-retouched avoid stiff ID-photo mood Lighting: soft Korean beauty lighting gentle facial brightness clean skin tone soft natural highlights on the face natural shadow transition subtle glow, but realistic skin texture avoid harsh flash avoid flat passport-photo lighting avoid dramatic studio glamour lighting Style: realistic photography clean studio portrait quality Korean influencer-style school portrait mood natural skin texture high detail seamless face and hair integration polished but believable Negative prompt: no identity loss no generic attractive face no over-beautified face no first-image hairstyle if different no awkward face blending no mismatched skin tone no mismatched hairline no distorted facial features no blurry eyes no deformed hands no extra fingers no change to the school uniform no change to the body pose no change to the background no cartoon style no anime style no text no watermark

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A cinematic travel moment through a beautiful heritage garden Capturing the architecture, flowers, and golden vibes in one smooth vlog. Created on seedance 2.0 Prompt: Create a 14-second cinematic travel vlog using the provided image as the exact location reference. Show a stylish young girl vlogging while walking through this beautiful heritage garden, keeping the same grand historic building, colorful flowers, wet pathway, greenery, palm trees and overall atmosphere from the reference image. Start with a wide establishing shot of the location, then show the girl smiling and talking naturally to her camera, turning the camera to reveal the beautiful surroundings. Include smooth walking shots, close-ups of flowers and architecture, natural reactions and a joyful spin. Use warm golden sunlight, realistic people, cinematic depth of field, smooth handheld/gimbal movement, natural ambient city sounds and ultra-realistic 4K quality. End with a beautiful wide shot of the same location. No text, no logos, no artificial-looking elements, and preserve the reference location accurately.

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BREAKING | New, high-quality footage and image has emerged of the 1. M88 engine of the shot down #Rafale from Bhatinda 2. Fuselage remains of aircraft 3. Crane carrying the debris of shot down Rafale (Image) 4. Eyewitness details of a local confirming the death of the pilot

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🧵 Go from nature to code with Gemini 2.5 Pro 🍃 Each of these were created with the same prompt: Transform this image into a code-based representation of its natural behavior. Original input image on the left. Gemini output on the right.

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The choreographer of Soda Pop mentioned that he made the dance while thinking of TWS "For Soda Pop, we were asked to create a choreography that feels fresh and easy to follow, with the vibe of a newly debuted idol group. If you think of a real group, the image is similar to TWS"

The choreographer of Soda Pop mentioned that he made the dance while thinking of TWS "For Soda Pop, we were asked to create a choreography that feels fresh and easy to follow, with the vibe of a newly debuted idol group. If you think of a real group, the image is similar to TWS"

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woww.. AI can literally do 3D rendering now just upload a draft 3D animation, it turns it into cinematic film scene you can control the looks of the car and environment with image refs no need days of rendering anymore..

woww.. AI can literally do 3D rendering now just upload a draft 3D animation, it turns it into cinematic film scene you can control the looks of the car and environment with image refs no need days of rendering anymore..

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MiniMax H3 Anime with Storyboard Making Omurice I kept the GPT Image 2 prompt for the storyboard extremely simple: "Create a rough sketch omurice-making storyboard with the given character." Even though the storyboard had panel numbers and a couple of small mistakes, H3 didn't have any issues with it. The video prompt was also very simple: "Use the storyboard @[storyboard ref] as sequential shot guidance, not as a static image. Do not treat the storyboard as one image. Follow each panel as a separate beat. Use @[character ref] as the character and visual style reference."

MiniMax H3 Anime with Storyboard Making Omurice I kept the GPT Image 2 prompt for the storyboard extremely simple: "Create a rough sketch omurice-making storyboard with the given character." Even though the storyboard had panel numbers and a couple of small mistakes, H3 didn't have any issues with it. The video prompt was also very simple: "Use the storyboard @[storyboard ref] as sequential shot guidance, not as a static image. Do not treat the storyboard as one image. Follow each panel as a separate beat. Use @[character ref] as the character and visual style reference."

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With the image editor of Grok Imagine, you can easily change the viewpoint of an image simply by requesting it. Here, a single image was created using the prompt, and then I requested different viewpoints.

With the image editor of Grok Imagine, you can easily change the viewpoint of an image simply by requesting it. Here, a single image was created using the prompt, and then I requested different viewpoints.

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AI is so trippy. This entire scene, including the exterior, was created from a single image of the ovens in the interior. This is a multi-view reconstruction, not a video. No v2v used. Prompt image in reply.

AI is so trippy. This entire scene, including the exterior, was created from a single image of the ovens in the interior. This is a multi-view reconstruction, not a video. No v2v used. Prompt image in reply.

martin_casado

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MiniMax H3 - Prompt Share Give it a character reference and it turns it into a high-tech digital assembly sequence. You can use parts of the result in your music videos too. Prompt: Use the provided reference as the final character target. Create a short premium cinematic character creation video where the character is built step by step through a high-tech digital assembly process. The sequence should feel fast, intense and visually sophisticated. Show a clear staged progression. Begin with abstract digital fragments, prototype sketches, blueprint-style drawings, construction lines and technical concept sheets appearing in the background. Then gradually assemble the character from the inside out, with limbs, body parts, clothing and facial features forming through scanning passes, holographic layers, wireframes, segmented image fragments, luminous particles and sleek interface elements. Let the arms, legs and other body parts visibly generate in stages, as if engineered by an advanced system. Some moments should show unfinished digital anatomy, partial structures and evolving forms before they lock into the final design. Keep the background alive with passing prototype art, silhouette studies, detail callouts and design variations to reinforce the feeling of a real creation process. The pacing should be rapid and aggressive, with dense motion, layered depth, sharp transitions and constant visual activity, while keeping the character build clearly readable as the main focus. The overall style should feel futuristic, polished, luxurious and cinematic. End with the fully completed character, cleanly revealed and clearly matching the reference.

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Now Iive: A new-look Community Reviews section! ✨ Coming soon: Better organisation and a lil’ polish on the rest of the book page.

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Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

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From flat image to animated 3D models in Spaces → Generate 3D models from an image or a prompt → Retexture, remesh, convert and UV unwrap on the canvas → Auto-rig your characters and apply animations → Snapshot any model into your image or video workflow Now on Magnific

From flat image to animated 3D models in Spaces → Generate 3D models from an image or a prompt → Retexture, remesh, convert and UV unwrap on the canvas → Auto-rig your characters and apply animations → Snapshot any model into your image or video workflow Now on Magnific

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