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最近一次命中来自 Vision：ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis
2026-04-09
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2026-04-10
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2026-04-11
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2026-04-12
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2026-04-13
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2026-04-14
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2026-04-15
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2026-04-17
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2026-04-18
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2026-04-19
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2026-04-20
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2026-04-21
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2026-04-22
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命中明细
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2026-04-22
ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis
Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-view data. Existing methods…
MMControl: Unified Multi-Modal Control for Joint Audio-Video Generation
Recent advances in Diffusion Transformers (DiTs) have enabled high-quality joint audio-video generation, producing videos with synchronized audio within a single model. However, e…
How Far Are Video Models from True Multimodal Reasoning?
Despite remarkable progress toward general-purpose video models, a critical question remains unanswered: how far are these models from achieving true multimodal reasoning? Existin…
CityRAG: Stepping Into a City via Spatially-Grounded Video Generation
We address the problem of generating a 3D-consistent, navigable environment that is spatially grounded: a simulation of a real location. Existing video generative models can produ…
2026-04-21
AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation
Video diffusion transformers (DiTs) suffer from prohibitive inference latency due to quadratic attention complexity. Existing sparse attention methods either overlook semantic sim…
OmniHuman: A Large-scale Dataset and Benchmark for Human-Centric Video Generation
Recent advancements in audio-video joint generation models have demonstrated impressive capabilities in content creation. However, generating high-fidelity human-centric videos in…
2026-04-17
Flow of Truth: Proactive Temporal Forensics for Image-to-Video Generation
The rapid rise of image-to-video (I2V) generation enables realistic videos to be created from a single image but also brings new forensic demands. Unlike static images, I2V conten…
2026-04-16
DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer
Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization holds important research val…
Seedance 2.0: Advancing Video Generation for World Complexity
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pr…
2026-04-15
Generative Refinement Networks for Visual Synthesis
While diffusion models dominate the field of visual generation, they are computationally inefficient, applying a uniform computational effort regardless of different complexity. I…
2026-04-14
OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation
In this work, we study Human-Object Interaction Video Generation (HOIVG), which aims to synthesize high-quality human-object interaction videos conditioned on text, reference imag…
HDR Video Generation via Latent Alignment with Logarithmic Encoding
High dynamic range (HDR) imagery offers a rich and faithful representation of scene radiance, but remains challenging for generative models due to its mismatch with the bounded, p…
2026-04-08
Action Images: End-to-End Policy Learning via Multiview Video Generation
World action models (WAMs) have emerged as a promising direction for robot policy learning, as they can leverage powerful video backbones to model the future states. However, exis…
OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control
Video fundamentally intertwines two crucial axes: the dynamic content of a scene and the camera motion through which it is observed. However, existing generation models often enta…
HumANDiff: Articulated Noise Diffusion for Motion-Consistent Human Video Generation
Despite tremendous recent progress in human video generation, generative video diffusion models still struggle to capture the dynamics and physics of human motions faithfully. In…