activity
20242026
most citedAMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Driving

1 citations · 1 across the 11 of their papers we have counts for

collaborators

17 papers

cs.CV2026

Drive3R: Block-wise Streaming Geometric Foundation Models for Autonomous Driving

Tianyi Yang, Haojun Yang, Jipeng Xiao +4

High-fidelity closed-loop simulation for autonomous driving increasingly relies on dense multi-view 3D reconstruction. While recent feed-forward geometric foundation models have re…

cs.CV2026

Spatial Memory Intelligence: Endowing World Models with Understanding-Driven Long-Term Memory

Ying Yang, Guiyu Zhang, Lianghua Huang +5

Long-video generation and world models have shown strong potential for interactive entertainment and embodied simulation by predicting future observations conditioned on user actio…

cs.CV2026

SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models

Junchao Huang, Guian Fang, Shengju Qian +15

We introduce SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference. Training across heterogeneous data s…

cs.CV2026

OptiGeo: Efficient Monocular Geometry for Embodied Perception in Optically Challenging Scenes

Muxin Liu, Tianbo Liu, Jing Xia +7

Monocular depth estimation has achieved strong open-domain generalization, yet reliable robotic deployment remains difficult in transparent, reflective, and specular environments,…

cs.CV2026

FoundationGeo: Learning Spatial Pixel-Wise Fields for Monocular Metric Geometry

Muxin Liu, Xiaoyang Lyu, Tianhe Ren +7

We present FoundationGeo, a two-stage framework that explicitly bridges relative and metric prediction via spatial calibration and principled data design. Stage 1 learns a high-fid…

cs.CV2026

DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving

Chen Shi, Jinrui Xu, Shaoshuai Shi +3

Pretrained foundation models have become an important basis for end-to-end autonomous driving. In contrast to vision-language models pretrained primarily on static image-text pairs…

cs.CV2026

Stabilizing Streaming Video Geometry via Dynamic Feature Normalization

Xiaoyang Lyu, Muxin Liu, Xiaoshan Wu +5

Consistent 3D geometry estimation from streaming RGB input is crucial for real-world applications such as autonomous driving, embodied AI, and large-scale reconstruction. While mod…

cs.CV2026

LIVE: Long-horizon Interactive Video World Modeling

Junchao Huang, Ziyang Ye, Xinting Hu +5

Autoregressive video world models predict future visual observations conditioned on actions. While effective over short horizons, these models often struggle with long-horizon gene…

cs.CV2025

GeoPredict: Leveraging Predictive Kinematics and 3D Gaussian Geometry for Precise VLA Manipulation

Jingjing Qian, Boyao Han, Chen Shi +4

Vision-Language-Action (VLA) models achieve strong generalization in robotic manipulation but remain largely reactive and 2D-centric, making them unreliable in tasks that require p…

cs.CV2025

UniSplat: Unified Spatio-Temporal Fusion via 3D Latent Scaffolds for Dynamic Driving Scene Reconstruction

Chen Shi, Shaoshuai Shi, Xiaoyang Lyu +4

Feed-forward 3D reconstruction for autonomous driving has advanced rapidly, yet existing methods struggle with the joint challenges of sparse, non-overlapping camera views and comp…

cs.CV2025

Memory Forcing: Spatio-Temporal Memory for Consistent Scene Generation on Minecraft

Junchao Huang, Xinting Hu, Boyao Han +4

Autoregressive video diffusion models have proved effective for world modeling and interactive scene generation, with Minecraft gameplay as a representative application. To faithfu…

cs.GR2025

Edit360: 2D Image Edits to 3D Assets from Any Angle

Junchao Huang, Xinting Hu, Shaoshuai Shi +2

Recent advances in diffusion models have significantly improved image generation and editing, but extending these capabilities to 3D assets remains challenging, especially for fine…

cs.CV2025

Enhancing Spatial Reasoning in Multimodal Large Language Models through Reasoning-based Segmentation

Zhenhua Ning, Zhuotao Tian, Shaoshuai Shi +4

Recent advances in point cloud perception have demonstrated remarkable progress in scene understanding through vision-language alignment leveraging large language models (LLMs). Ho…

cs.CV2025

Proteus-ID: ID-Consistent and Motion-Coherent Video Customization

Guiyu Zhang, Chen Shi, Zijian Jiang +4

Video identity customization seeks to synthesize realistic, temporally coherent videos of a specific subject, given a single reference image and a text prompt. This task presents t…

cs.CV2025

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

Chen Shi, Shaoshuai Shi, Kehua Sheng +2

Data-driven learning has advanced autonomous driving, yet task-specific models struggle with out-of-distribution scenarios due to their narrow optimization objectives and reliance…

cs.CV2025

JiSAM: Alleviate Labeling Burden and Corner Case Problems in Autonomous Driving via Minimal Real-World Data

Runjian Chen, Wenqi Shao, Bo Zhang +3

Deep-learning-based autonomous driving (AD) perception introduces a promising picture for safe and environment-friendly transportation. However, the over-reliance on real labeled d…

cs.CV2024★ 1 cited

AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Driving

Xiaosong Jia, Shaoshuai Shi, Zijun Chen +4

As an essential task in autonomous driving (AD), motion prediction aims to predict the future states of surround objects for navigation. One natural solution is to estimate the pos…