From the 1 of 13 linked papers with an AI index.
6 papers · 1 filter
PerceptDrive: Perception Prior World-Action Modeling with Adaptive Expert Routing for End-to-End Autonomous Driving
Yushan Liu, Tianxiong Lv, Bohua Wang +11
Frozen perception foundation models encode rich geometric, semantic, and dynamic knowledge. Yet narrow conditioning interfaces may attenuate task-relevant cues, while static fusion…
ABot-N1: Toward a General Visual Language Navigation Foundation Model
Ruiyan Gong, Yingnan Guo, Junjun Hu +44
The paper presents ABot-N1, a visual‑language navigation foundation model that separates high‑level reasoning from low‑level control via a slow‑fast architecture and pixel‑based go…
ForgeDrive: Bidirectional Cross-Conditioning for Unified Visual-Action Generation in Autonomous Driving
Xuchang Zhong, He Zheng, Chenxu Zhao +9
World-model-based autonomous driving endows the model with the ability to understand scene evolution. Yet this promise is undermined by the prevailing imagine-then-act paradigm, wh…
DiffVL: Diffusion-Based Visual Localization on 2D Maps via BEV-Conditioned GPS Denoising
Li Gao, Hongyang Sun, Liu Liu +2
Accurate visual localization is crucial for autonomous driving, yet existing methods face a fundamental dilemma: While high-definition (HD) maps provide high-precision localization…
Smooth Operator: Smooth Verifiable Reward Activates Spatial Reasoning Ability of Vision-Language Model
Siwen Jiao, Tianxiong Lv, Kangan Qian +7
Vision-Language Models (VLMs) face a critical bottleneck in achieving precise numerical prediction for 3D scene understanding. Traditional reinforcement learning (RL) approaches, p…
VideoPerceiver: Enhancing Fine-Grained Temporal Perception in Video Multimodal Large Language Models
Fufangchen Zhao, Liao Zhang, Daiqi Shi +5
We propose VideoPerceiver, a novel video multimodal large language model (VMLLM) that enhances fine-grained perception in video understanding, addressing VMLLMs' limited ability to…