Hugging Face Trending Papers
WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory
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arXiv Computer Vision
5d ago
WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory
WorldCrafter is a video world model that introduces a camera‑queryable implicit 3D‑aware memory to improve long‑horizon consistency and viewpoint control. The model compresses multi‑view evidence into a limited token budget shaped by the requested viewpoint, integrating historical observations via a memory encoder and pose‑conditioned readout before denoising. Experiments on static and dynamic scenes demonstrate significant gains in consistency and camera‑control accuracy while maintaining visual quality during minute‑scale exploration.
arXiv Machine Learning
Jul 23
WorldPack: Dynamic Frame Compression for Long-context Video World Modeling
arXiv:2512. 02473v2 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on past observations and navigation actions.
arXiv Computer Vision
Sep 1
Matrix-Game 3.5: Enhancing Real-Time Streaming Interactive World Models with Patch Memory
arXiv:2608.29910v1 Announce Type: new Abstract: Interactive world models extend video generation from offline clip synthesis toward persistent simulation of interactive virtual worlds, enabling appli...
arXiv Computer Vision
Sep 11
World in World: Explore the World with World Models
World in World introduces a training‑free, inference‑time interface that transforms diverse control signals—such as source‑video observations, target‑view projections, geometry renderings, and retrieved states—into camera‑ and time‑labelled visual states. These states are processed by a frozen causal video model’s self‑attention, enabling tasks like camera‑controlled rerendering, long‑horizon revisiting, and human‑motion transfer without additional training. The method employs a correspondence router and evidence‑wise attention to align token identities and regulate auxiliary channel contributions during a single denoising pass.
arXiv Machine Learning
Jun 9
Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models
arXiv:2605. 31158v2 Announce Type: replace-cross Abstract: Interactive video world models generate video chunk by chunk in response to user-controlled camera movements, enabling applications such as real-time game simulation, virtual scene navigation, and embodied AI training.
Hugging Face Trending Papers
Sep 10
World in World: Explore the World with World Models
World in World introduces a training‑free inference interface that lets users control autoregressive video world models from new viewpoints. By converting diverse control signals—source‑video observations, target‑view projections, geometry renderings, and retrieved states—into camera‑ and time‑labelled visual tokens, the system uses a frozen causal video model’s self‑attention to maintain synchronization, complete unseen regions, and recover past appearances. The method supports camera‑controlled rerendering, long‑horizon revisiting, and human‑motion transfer while preserving perceptual quality, temporal consistency, and camera‑following accuracy.