12 papers
PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space
Sensen Gao, Zhaoqing Wang, Qihang Cao +3
3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generation. Recent works attempt to…
Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
Kewei Zhang, Jin Wang, Sensen Gao +9
End-to-end autonomous driving via Vision-Language-Action (VLA) models demands a precarious balance between high-fidelity trajectory planning and efficient inference. Existing parad…
Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding
Sensen Gao, Shanshan Zhao, Xu Jiang +7
Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines feeding Large Language Models (…
Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective
Weijie Wang, Qihang Cao, Sensen Gao +10
Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and interacting with the physical…
Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM
Chengyue Wu, Shiyi Lan, Yonggan Fu +9
Vision-language models (VLMs) predominantly rely on autoregressive decoding, which generates tokens one at a time and fundamentally limits inference throughput. This limitation is…
OneWorld: Taming Scene Generation with 3D Unified Representation Autoencoder
Sensen Gao, Zhaoqing Wang, Qihang Cao +5
Existing diffusion-based 3D scene generation methods primarily operate in 2D image/video latent spaces, which makes maintaining cross-view appearance and geometric consistency inhe…