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Ring Forcing is an autoregressive video diffusion framework that enhances long-term memory for precise minute-long video coherence through ring-structured training, history compression, and sparse rotary embeddings.
4DAnyone reconstructs 4D humans from monocular video by generating multiview-consistent videos and lifting them into 4D Gaussian Splatting, using reference and target context designs to address scaling bottlenecks.
AnyTalk generates 3D speech animations for arbitrary characters without requiring animation data by adapting video diffusion models through character-specific fine-tuning and optimizing blendshape parameters, with a real-time distilled variant.
Marionette introduces a world model that explicitly predicts 3D articulated states for interactive games, decouples geometry rendering with a zero-parameter renderer, and uses diffusion for appearance synthesis, improving controllability and long-horizon consistency.
SCoPE is a model from TencentARC that adds camera sightlines as positional coordinates to a pretrained video diffusion transformer, enabling camera trajectory control while preserving the image-to-video prior. The release includes a self-contained checkpoint for Wan2.2-I2V-A14B inference.
LiveAnimate presents a 14B-parameter video diffusion transformer enabling real-time, long-form pose-driven human animation with stable streaming and constant memory usage via PR-Sink attention. Achieves 19.63 FPS inference on two H100 GPUs, maintaining quality over three-minute streams.
This paper introduces Latent-to-4D, a method for direct 4D scene generation from video diffusion latents without retraining across generators, achieving better geometry and temporal stability than cascaded approaches.
MirrorWorld is a reflection-aware video inpainting framework that improves mirror reflection generation in videos by separately modeling semantic content (SRD) and geometric spatial arrangements (GTA), achieving better reflection reconstruction than existing image-based and video inpainting baselines.
Introduces UniWorld-View, a unified framework for large-baseline novel view synthesis from monocular inputs, integrating occlusion-aware point cloud rendering with video diffusion models for precise camera control and geometric consistency.
TenStrip/10Eros-Max is an experimental AI model that modifies the MiniMax H3 base model by transferring learned patterns from LTX 2.3, Wan 2.2, and Krea 2 video and image diffusion models using orthogonal projection, enhancing aesthetic and motion character while preserving core video and audio capabilities.
This paper proposes 'Mirror Learning', a framework for imitation learning from third-person observation that uses a fine-tuned video diffusion model for perspective transformation and an inverse dynamics model to synthesize pseudo first-person expert data, showing that this mirror data alone can train effective policies and improve behavior cloning.
DreamTraj predicts 6-DoF object trajectories from a single RGB image and a language instruction by decoding internal video diffusion latents, eliminating the need for video, depth, or CAD models at inference. It introduces the MOVEdataset with fine-grained language-to-motion annotations and achieves state-of-the-art performance while running 4.6x faster than generate-then-extract pipelines.
This paper introduces a rest-state framework that reconstructs articulated objects from a single closed configuration, using explicit meshes, vision-language outputs, and video diffusion models to generate and validate articulation hypotheses without observed motion.
WorldWeaver (W²) introduces cross-agent world state registers to multi-agent video diffusion models, enabling shared world state persistence across agents and views, improving logical consistency in two-agent Minecraft video generation.
Sol-Engine weekly update announces integration of Sol Attention, a training-free sparse attention method for video diffusion, with full paper coming next week.
AlayaWorld is a 15B-parameter interactive video world model that generates 24-fps video at 540p and 720p, using autoregressive latent chunk generation with bounded visual context and distillation to reduce inference steps. It achieves state-of-the-art performance on the iWorld-Bench for long-horizon generation.
Proposes StudioRecon, a method for 4D human-scene reconstruction from low-overlap camera captures, using separate priors for backgrounds (video diffusion) and humans (SMPL), with a recursive enhancement module. Accepted to SIGGRAPH 2026, outperforming prior methods by +1.5 to +5.0 dB PSNR.
Flex-Forcing introduces a unified framework for video diffusion that supports both autoregressive and bidirectional generation modes, offering flexible control for video generation tasks.
LongE2V leverages pre-trained video diffusion priors and introduces Autoregressive Unrolling, Adaptive Context Switching, Reencoding Alignment, and Event Voxel Density Augmentation to achieve high-quality video reconstruction, prediction, and frame interpolation from sparse event streams, outperforming state-of-the-art methods.
LingBot-Video is a 13B sparse-MoE video diffusion transformer (1.4B active) post-trained with RL as an action-conditioned world model, open-sourced with weights and code. It includes a physical-plausibility reward graded by a VLM and frames itself as a policy evaluator and action planner, though closed-loop robot results are absent.