collaborators

12 papers

cs.CV2026

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model

Senqiao Yang, Kaichen Zhang, Zhaoyang Jia +20

Standard vision-language models (VLMs) suffer from Moravec's paradox: they excel at complex offline visual reasoning but struggle with simple streaming perception tasks and process…

cs.CV2026

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing

Xinjie Zhang, Peng Zhang, Shicheng Zheng +21

Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to…

cs.CV2026

MambaRaw: Selective State Space Modeling for Efficient 4K Raw Image Reconstruction

Peize Li, Fanhu Zeng, Tongda Xu +5

In-camera JPEG previews are ubiquitous in raw image formats and provide an sRGB reference at negligible storage cost. Although existing metadata-based reconstruction frameworks can…

cs.CV2026

SenseFlow: Scaling Distribution Matching for Flow-based Text-to-Image Distillation

Xingtong Ge, Xin Zhang, Tongda Xu +4

The Distribution Matching Distillation (DMD) has been successfully applied to text-to-image diffusion models such as Stable Diffusion (SD) 1.5. However, vanilla DMD suffers from co…

cs.CV2025

GaussianImage++: Boosted Image Representation and Compression with 2D Gaussian Splatting

Tiantian Li, Xinjie Zhang, Xingtong Ge +4

Implicit neural representations (INRs) have achieved remarkable success in image representation and compression, but they require substantial training time and memory. Meanwhile, r…

cs.CV2025

Feed-Forward 3D Gaussian Splatting Compression with Long-Context Modeling

Zhening Liu, Rui Song, Yushi Huang +5

3D Gaussian Splatting (3DGS) has emerged as a revolutionary 3D representation. However, its substantial data size poses a major barrier to widespread adoption. While feed-forward 3…