Creating a 3D model at the touch of a button from just one photo with AI - what sounded futuristic a short time ago is now becoming a reality thanks to AI. Modern web platforms promise to automatically create 3D meshes with texture from 2D images. These services analyze an uploaded image (or several) using AI and reconstruct a three-dimensional object from it, including a colored surface texture.
The basic idea behind all services is similar: a neural network analyzes the submitted image and generates a 3D object from it. Some platforms also accept text prompts or multiple images. From these, volumetric representations are calculated, which are converted into a polygon mesh and provided with textures. The models are typically exported in formats such as OBJ, FBX, GLTF or STL.
Tripo AI was one of the first publicly available AI platforms for generative 3D models at the end of 2023. The service advertises extremely fast conversion: a complete 3D model is supposed to be created from a photo or text description in less than 10 seconds. According to Tripo, its AI has been trained with millions of data sets from animation and video game assets in order to achieve a high level of detail. In fact, Tripo promises "high geometric complexity and photorealistic textures" in the generated models. In practice, this means that if you enter a photo of a chair, for example, you get a mesh with a large number of polygons that reproduces fine shapes, as well as a color texture that closely resembles the photo (including shading and materials).
Tripo provides common formats for export - including GLB, FBX, OBJ, USD (Universal Scene Description), STL and even Minecraft schematics. Tripo thus aims to make the generated models directly usable in a wide variety of environments, from game engines and AR/MR applications to 3D printing and even specific ecosystems such as Roblox or Minecraft. In Tripo's user interface, in addition to uploading an image, you can also enter text instead (text-to-3D) or - for better results - upload multiple images from different perspectives. The latter helps to fill in gaps: If you have front and back views of an object, for example, the AI can reconstruct much more accurately than with just one view.
Tripo also offers simple editing tools to customize the generated model. For example, the result can be scaled, rotated or refined to a certain extent directly in the browser before downloading if something is not ideal. The models from Tripo are "professional-grade" enough that they can be used directly in 3D pipelines - for example, animated in a game engine or further processed in Blender.
Tripo has a freemium model for use: the free account currently gives you 10 generations per month for free. There are also paid packages with a higher quota (e.g. 100 models/month). Tripo also offers the prospect of an API, which is aimed at integration into your own apps and workflows. Overall, Tripo positions itself as an all-purpose tool for fast 3D content creation. The speed is particularly impressive - in tests, the 3D model is actually available after a few seconds of computing time, which is a quantum leap compared to classic photogrammetry tools (which often take minutes to hours).
Hyper3D is another AI platform that generates general 3D models from images and text in a similar way to Tripo. Hyper3D is backed by the company Deemos, which calls its AI technology Rodin. A particular highlight of Hyper3D is the module ChatAvatar - a specialized generator for 3D faces and avatars. ChatAvatar can create a hyper-realistic 3D face model from a portrait photo (or even from a textual description of a person). According to the provider, these digital heads are "production-ready" and equipped with PBR textures, meaning they are ready for use in games, film or VR. Technically, ChatAvatar is based on current research that makes progressive improvements to the 3D face. The result is an animatable 3D model of the face - including realistic skin details, hair and facial features. Such avatars can be animated using Blendshape morphs or a rig to display facial expressions, for example. Hyper3D even offers direct plugins for common tools: There are integrations for Daz3D, Unity, Blender, Maya, Cocos, Unreal, Omniverse and iClone to seamlessly transfer the generated 3D avatars.
But Hyper3D can do more than just heads: the Rodin platform also generates general 3D objects from text or images, similar to Tripo and Meshy. An example would be entering "a futuristic robot" as a text prompt - Hyper3D generates a complete robot model from this. The user interface offers options such as symmetry enforcement (e.g. to obtain symmetrical models for frontal images) and also supports multi-view input for more precise results. The speed ranges from a few seconds to a few minutes, depending on model complexity. It is interesting to note that Hyper3D stands out with continuous versions of its AI model: Rodin Gen-1.5 is currently available, which brings significant improvements in topology and texture (including an option for quad meshes with clean topology).
Hyper3D's business model is based on a credit system. There is a limited free trial, after which subscriptions are available at various levels (Creator, Business, etc.), which offer a quota of credits per month. One innovative idea is the "pay-by-result" principle: you can generate several trials and only pay for the model that is finally accepted. This means you don't have to waste credits if a first run doesn't work - a clear indication that iterative attempts are often necessary. In addition to ChatAvatar (version 0.7 beta), Hyper3D is also planning a service called HyperHuman, which will generate complete bodies and digital characters in the future. However, it is already possible to create digital doubles using Rodin + ChatAvatar: e.g. generate a head via ChatAvatar and mount it on a generic body.
Overall, Hyper3D is aimed at professional users who need high-quality, animatable 3D avatars and objects and are prepared to accept a slight reduction in speed (compared to Tripo, for example).
Meshy confidently describes himself as "#1 AI 3D Model Generator for Creators" and is aimed at game developers, 3D printing enthusiasts and XR creators alike. The special thing about Meshy is the multitude of functions under one roof:
Picture-to-3DDetailed 3D models can be generated from individual images or concept artwork. Meshy states that only "a few seconds" per model - usually less than one minute.
Text-to-3DAs with the others, you can also use a textual description as input to create an object instead.
Text-to-texture: Here you can upload an existing mesh and the AI can create new meshes with a text prompt. Material textures can be created for this purpose. For example, you could upload an untextured 3D tree and create it with "mossy, old oak bark" Meshy would generate corresponding diffuse/normal maps. This feature is useful to retrofitting with your own models.
AnimationMeshy offers a one-click rigging solution for bipedal or quadrupedal characters. For example, if you have generated a 3D model of a character, the system can automatically insert a skeleton and even animate a simple walk cycle. This allows you to quickly create a walking figure without manual rigging. For developers building prototypes, this is a huge time saver.
The platform also impresses with some Quality-of-Life Features: PBR support (several maps are automatically generated for a more realistic display), Style options (you can specify in advance whether the output should be realistic, cartoon-like, voxel-like, anime-style, etc.), Multilingual interface (Prompts can also be entered in German, for example), API-access for developers and Plugins (Plugins are available for Blender and Unity to use Meshy directly there). The brand new Apple Vision Pro has also been considered - there is a VisionOS app for exploring 3D models in AR. Meshy is just as generous when it comes to export: in addition to OBJ/FBX/GLB/STL, even USDZ (Apple AR format) and BLEND (Blender project file), which is very convenient for various workflows.
In terms of performance, Meshy has often scored highly in community tests. In a comparison by Reddit users, for example, an identical image was run through various generators - Meshy already delivered better results here than some of the competition, but in one case did not quite come close to Tripo. However, Meshy's developers emphasize that they are constantly working on improvements and using feedback from such tests. In fact, Meshy recently launched a special "Hard Surface Mode" introduced to Clearer topology and details for technical or angular objects. According to Meshy, this mode provides a "significant leap in mesh quality" and generates much cleaner models from photos of buildings or machines, for example. This shows that the platform actively addresses the typical weaknesses of AI models.
How close do the automatically generated models come to hand-made 3D assets? This question immediately arises for every professional. The short answer: Amazingly close - but with limitations. In the best case, a model is obtained in seconds that is suitable for Prototyping, concept visualization or simple applications can be used directly. For high-end productions, on the other hand, manual rework is often necessary. Here are some typical aspects of quality:
Number of polygonsAI tends to do this, very high resolution meshes. Finally, the model attempts to geometrically reproduce every last detail of the image. The result can be meshes with hundreds of thousands of triangles. This is often too much for real-time applications (games, XR) - a manual Retopology or decimation is advisable to make the model "game-ready". Hyper3D has recognized this and with Rodin Gen-1.5 a step in the direction of Automatic topology optimization done (keyword AI Quad Mesh). Nevertheless: Currently, the models are mostly not low-poly.
Topology and cleanliness: Closely related to this is the Network quality. Generative models care little about beautiful edge loops or animatability; they spit out triangular meshes that may not be internally manifold or illogically structured. Messy topology can be seen, for example, in the form of unnecessarily jagged surfaces, doubled polygons or tangled triangles in areas that are actually smooth. This may not matter for static objects - but if you want to rig and animate a character model, you quickly reach the limits because the deformation of unclean topology causes artifacts. This is where a 3D artist usually has to rework.
Texture qualityAI textures are often surprisingly good in filling in details, but can also blurred or have uneven areas. For example, lettering or fine patterns on the original image are difficult for the AI to reconstruct exactly - they then appear washed out. Exposure effects of the photo (highlights, shadows) can also "burn" into the texture, as the AI does not always separate these perfectly from actual color details. Some services therefore recommend using photos that are as evenly lit as possible (e.g. ChatAvatar: "clear portraits with bright lighting and no shadows work best). On the positive side, some PBR textures are included - such as normal maps, which means that the fine structure does not have to be fully baked into the mesh, but is displayed using bump mapping. Meshy, for example, automatically generates complete PBR map sets for more realistic results. Overall, the Color textures of the AI models are often useful as a starting point, but for photorealistic requirements they would still need to be touched up in Photoshop or Substance Painter.
Special cases (faces and co.): Particularly demanding are human faces or organic creatures in general. While an AI model of a shoe or chair can turn out very neat, generated people/characters often still look a bit uncanny or flawed. Faces might be asymmetrical, eyes and teeth sometimes appear "washed out" on the texture, and hair is a known problem (often represented only as a coarse mass without fine strands). This is exactly why specialized solutions like Hyper3D's exist ChatAvatarwho want to solve such cases better with specially trained models. But the same applies here: not every generated face is immediately convincing for use as an animated main character - but they can certainly suffice for secondary characters or background NPCs in a simulation.
Geometry of the non-visible sides: An image usually only shows one view of an object; the AI must therefore be able to recognize the hidden areas hallucinate. It can happen that backs or undersides are very simple or wrong - e.g. a photo model of an armchair suddenly has no real backrest because only the front was visible in the photo. Some tools try to use general priors to create something sensible here (such as the back being symmetrical to the front), but no one can guarantee it. Therefore, several input images (all-round photos) provide better results, or you have to do it yourself afterwards to correct gaps or errors in hidden areas.
Despite these weaknesses, it must be emphasized: Quality has made huge progress in a short space of time. In 2022, AI 3D models were still mostly lumpy and extremely limited; today, we can see some real impressive details and structures that at first glance could be equated with a handmade asset. For stylized assets (e.g. cartoon style, voxel look), the generation often works particularly well, as minor inaccuracies are less noticeable here or even contribute to the charm. But even realistic objects - such as a complex engine or a figure in armor - can now be pre-constructed surprisingly well by AI. It is important to manage expectations correctly: a 100% perfect, optimized production model you don't (yet) get. But you might save 80% of time because you already get a rough basic framework from the AI, which you then just have to optimize
As with AI-generated 2D images, the same applies here: The results may vary from round to round. If you start the same request twice, the AI can output different interpretations - sometimes version A is more successful, sometimes version B. Factors such as slight differences in the prompt or image cropping can already have an influence. It is therefore common, several attempts to plan. Many users report that they upload a motif several times, possibly with slightly different settings, in order to select the best result. The platforms themselves recognize this need: Hyper3D, for example, allows you to regenerate until you are satisfied and only then charges a credit. You could say that using it sometimes feels like a Gambling with a very high chance of winning - one rolls the dice new AI models until there is one that meets the requirements. Especially if you want a very specific object, you may have to refine the text prompt or try out other reference images to steer the AI model in the desired direction.
There can also be differences between different platforms as to which model copes better with which subject. In a Reddit comparison, for example, it was found that with a certain image Tripo delivered the most convincing model, while Meshy came out on top in another. So there is no harm in testing several tools - especially as all of the tools presented here offer a free scope of use.
Overall, you should be aware that Generative AI always involves a degree of experimentation. The models are probabilistic - in other words, there is no the one The result is not the right solution, but a range of possible 3D outputs for a given input. This variance can be frustrating if you're in a hurry, but it's also part of the creative potential: you might unexpectedly get a variant that sparks new ideas. It is important to allow enough time for iterations instead of blindly trusting the first output.
The ability to generate fully-fledged 3D models from 2D images using AI is still in its infancy, is already revolutionizing content creation. For professionals in the XR and 3D sector, tools such as Tripo, Hyper3D and Meshy offer an exciting Productivity boost - Routine modeling tasks can be accelerated and initial drafts can be created in minutes instead of days. Generative 3D models are worth their weight in gold, especially in early concept phases or for prototypes in VR/AR applications. Instead of time-consuming modeling or resorting to prefabricated assets, something suitable can be quickly generated and exchanged until it is right. Also Non-experts A UX designer can, for example, have their sketch of an object translated into 3D by the AI without having to operate 3D software themselves.
At the same time, you have to remain realistic: Production maturity in the sense of Plug-and-play for final projects has not yet been achieved. If you need the highest quality or optimized performance, you can hardly avoid manual reworking at the moment. The AI serves as a Assistantnot as a complete replacement for a 3D artist. But as with AI image generators, we are seeing rapid progress. Updates are released annually (if not quarterly) that improve resolution, topology and material fidelity. It is foreseeable that in a few years many of today's weaknesses will be significantly reduced - similar to how early digital photos were once pixelated and poor in color and are now high-resolution and clear.
The bottom line is that we draw a Cautiously optimistic balance sheet: The platforms presented Tripo, Hyper3D/ChatAvatar and Meshy show what is already possible and pave the way for a new kind of 3D content creation. For the XR industry, which has an immense appetite for 3D content, this is a potential Game Changer. The technology is not yet perfect and the results are sometimes erratic - but the direction is right. It is worth keeping an eye on these developments and experimenting with them in projects now. The future of 3D creation is AI-supportedand we are only at the beginning of this exciting journey.
Are you interested in developing a virtual reality or 360° application? You may still have questions about budget and implementation. Feel free to contact me.
I am looking forward to you
Clarence Dadson CEO Design4real
