activity
20242026
collaborators

6 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.IR2025

POQD: Performance-Oriented Query Decomposer for Multi-vector retrieval

Yaoyang Liu, Junlin Li, Yinjun Wu +1

Although Multi-Vector Retrieval (MVR) has achieved the state of the art on many information retrieval (IR) tasks, its performance highly depends on how to decompose queries into sm…

cs.CV2024

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…