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From the 1 of 10 linked papers with an AI index.

collaborators

10 papers

cs.CV2026

ContextMaster: Interactive Multi-Shot Video Creation via Fixed-Budget Sparse Context Routing

Xu Guo, Zhengxuan Wei, Xinghui Li +11

Recent video models increasingly support generation, reference conditioning, and editing within a single model, yet typically expose them as separate operations over fixed inputs.…

cs.MM2026

Conan-embedding-v3: Fusing Modality-Specific Models for Omni-Modal Embedding

Shiyu Li, Zhiyuan Hu, Yifan Wang +3

The paper presents Conan-embedding-v3, a framework that trains modality‑specific specialist models, fuses them into a single dense backbone, and then recovers the modality projecto…

cs.CV2026

Focus When Necessary: Adaptive Routing and Collaborative Grounding for Training-Free Visual Grounding

Yifan Wang, Peiming Li, Shiyu Li +5

While Multimodal Large Language Models (MLLMs) excel in cross-modal reasoning, they often struggle to perceive fine-grained details in complex high-resolution images. Recent traini…

cs.CV2026

VideoWeave: Unlocking Geometric Consistency in Video Generation via Joint Geometry-Video Modeling

Xunzhi Xiang, Zixuan Duan, Yabo Chen +8

Large-scale video diffusion models often fail to preserve 3D structure over time, causing geometric drift and implausible motion under viewpoint changes. Existing methods usually e…

cs.CV2026

SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models

Zhengxuan Wei, Yi Dong, Zonghui Li +6

Low-Rank Adaptation (LoRA) merging can efficiently combine diverse generative capabilities from multiple trained LoRAs for a diffusion model. However, existing LoRA merging techniq…

cs.CV2026

Geometry-Aware Implicit Memory for Video World Models

Zhengxuan Wei, Xu Guo, Xinghui Li +8

Video world models aim to simulate controllable visual environments, but long-horizon rollouts depend on what the model remembers after observations leave its native context window…