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RAR: Rate-Adaptive Rollout for Time-Consistent Interactive World Models
Yaoyang Liu, Dongyu Yan, Yihua Du +5
Video-based interactive world models aim to enable real-time, user-controllable environments. Yet most existing systems are trained and rolled out at a fixed temporal rate, limitin…
SwiftI2V: Efficient High-Resolution Image-to-Video Generation via Conditional Segment-wise Generation
YaoYang Liu, Yuechen Zhang, Wenbo Li +3
High-resolution image-to-video (I2V) generation aims to synthesize realistic temporal dynamics while preserving fine-grained appearance details of the input image. At 2K resolution…
MIRAGE: Runtime Scheduling for Multi-Vector Image Retrieval with Hierarchical Decomposition
Maoliang Li, Ke Li, Yaoyang Liu +5
To effectively leverage user-specific data, retrieval augmented generation (RAG) is employed in multimodal large language model (MLLM) applications. However, conventional retrieval…
V2P-Bench: Evaluating Video-Language Understanding with Visual Prompts for Better Human-Model Interaction
Yiming Zhao, Yu Zeng, Yukun Qi +8
Large Vision-Language Models (LVLMs) have made significant strides in the field of video understanding in recent times. Nevertheless, existing video benchmarks predominantly rely o…
MagicMirror: ID-Preserved Video Generation in Video Diffusion Transformers
Yuechen Zhang, Yaoyang Liu, Bin Xia +4
We present MagicMirror, a framework for generating identity-preserved videos with cinematic-level quality and dynamic motion. While recent advances in video diffusion models have s…
ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
Shenghai Yuan, Jinfa Huang, Yongqi Xu +7
We propose a novel text-to-video (T2V) generation benchmark, ChronoMagic-Bench, to evaluate the temporal and metamorphic capabilities of the T2V models (e.g. Sora and Lumiere) in t…