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Why panorama? Standard video models struggle with object permanence—if a camera pans away and comes back, objects may disappear. With panoramas, the model is forced to generate everything in the scene. This serves as a "working memory" for consistent world generation. (3/N)

Ziyi Wu

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22,019 görüntüleme • 6 ay önce •via X (Twitter)

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Restyling games is much harder than generating a video. Games can’t unintentionally “reset” at every frame: • Your character should stay the same when the camera moves • Damage, lighting, and objects must persist • A room should look the same when you look away and look back And it all has to run in real-time. Reverie v0.1.0 is our first stab at a real-time generative model for playable worlds. Below is a comparison with ours (left) with MirageLSD v2 (right). It’s early and far from perfect but watch what stays consistent as the video continues. 🧵 Prompts below (GPT-5.2).

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✨ CVPR 2025 highlight: A Distractor-Aware Memory for Visual Object Tracking with SAM2 the authors propose a new distractor-aware memory model for SAM2 and an introspection-based update strategy that jointly addresses the segmentation accuracy as well as tracking robustness 🏡 (1/n)🧵👇

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Over the past two years, AI video models have been competing on realism, resolution, and duration. But no matter how impressive the results look, we remain passive viewers: we press play, watch the clip, and it ends. AlayaWorld Alaya Lab is attempting something fundamentally different. Instead of generating a fixed video, it generates a world that continues to unfold as you move through it. These three demos show the same journey toward a green village rendered in three distinct styles: photorealistic, oil painting, and line art. As the camera moves forward, the model continues generating the road, fences, trees, and distant village. This is not simply an existing video with different filters applied. The environment is generated continuously along the camera trajectory, allowing the scene to develop as the user explores it. AlayaWorld streams video at 720p and 24 FPS while supporting camera movement and viewpoint control. The real breakthrough is not just image quality. Once generation becomes fast enough to respond within an interactive loop, the user is no longer merely watching a video. They become a participant inside the generated world. The world can also respond to new instructions. During generation, users can introduce prompts that trigger spells, summon characters, create explosions, or transform the environment. Most video models follow an initial prompt and produce a predetermined clip. AlayaWorld can respond to changing intent while the world is still running, allowing subsequent events to evolve according to the user’s commands. Generating an attractive frame is relatively easy. Maintaining a coherent world over time is much harder. As a video model repeatedly predicts the next frame, small errors can accumulate until roads, buildings, and objects begin to distort or disappear. AlayaWorld combines spatial memory with compressed historical context, helping the model remember both where things are and what has already happened. This enables stable generation lasting more than one minute while improving consistency when the camera leaves an area and later returns. This may be the next step for AI video: not simply generating a longer movie, but generating a world that can be explored, changed, and interacted with. AlayaWorld is developed by Alaya Lab. The team is progressively releasing its inference code, training code, and datasets, with an online experience expected to launch near the end of the month. Project page:

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Meet Gemini Omni Flash on SeaArt. A natively multimodal model for video generation and conversational editing. Edit with natural language. Keep scenes and story consistent across edits. Motion follows real-world physics and logic. From prompt to scene — in one flow.

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Nairobi becomes the convening point for one of the most consequential conversations for Africa in this generation. More than 30 Heads of States, coming together to discuss 7 agenda themes with 1 vision - Taking #AfricaFoward. We have spent months working to ensure that when the world comes to Nairobi on 11 and 12th May, Africa arrives as a continent with a clear vision of its priorities, and the partners committed to advancing them alongside us. This is a Summit of substance, one with the potential to define a new chapter in Africa’s global engagement.

Nairobi becomes the convening point for one of the most consequential conversations for Africa in this generation. More than 30 Heads of States, coming together to discuss 7 agenda themes with 1 vision - Taking #AfricaFoward. We have spent months working to ensure that when the world comes to Nairobi on 11 and 12th May, Africa arrives as a continent with a clear vision of its priorities, and the partners committed to advancing them alongside us. This is a Summit of substance, one with the potential to define a new chapter in Africa’s global engagement.

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Most generative models predict pixels. Predicting a 3D scene instead has many benefits: the scene won’t change if you look away and come back, and it obeys the basic physical rules of 3D geometry. The simplest way to visualize the 3D scene is a depth map, where each pixel is colored by its distance to the camera. 4/n

Most generative models predict pixels. Predicting a 3D scene instead has many benefits: the scene won’t change if you look away and come back, and it obeys the basic physical rules of 3D geometry. The simplest way to visualize the 3D scene is a depth map, where each pixel is colored by its distance to the camera. 4/n

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New open-source 3D world-generation model. I'm rendering a couple of worlds in the video, so check it out. You'll find the GitHub and the Hugging Face links to the model below. This is a multi-modal world model that you can use for a bunch of things: • To generate new worlds • To reconstruct worlds • To simulate 3D interactive worlds from a prompt, images, or a video You can edit the 3D outputs in Unity and Unreal Engine (they export as meshes, 3DGS files, and point clouds). You can also generate 3D characters in the world and walk around. Pretty fun stuff!

New open-source 3D world-generation model. I'm rendering a couple of worlds in the video, so check it out. You'll find the GitHub and the Hugging Face links to the model below. This is a multi-modal world model that you can use for a bunch of things: • To generate new worlds • To reconstruct worlds • To simulate 3D interactive worlds from a prompt, images, or a video You can edit the 3D outputs in Unity and Unreal Engine (they export as meshes, 3DGS files, and point clouds). You can also generate 3D characters in the world and walk around. Pretty fun stuff!

Santiago

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Introducing WildDet3D, a grounding model for monocular 3D object detection in the wild. A question I keep coming back to is: what is the right backbone for robotics foundation models? Should it be a video model, a language model, or perhaps a grounding model? WildDet3D is our first step in exploring that direction.

Introducing WildDet3D, a grounding model for monocular 3D object detection in the wild. A question I keep coming back to is: what is the right backbone for robotics foundation models? Should it be a video model, a language model, or perhaps a grounding model? WildDet3D is our first step in exploring that direction.

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