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20232026
most citedPonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm

6 citations · 14 across the 19 of their papers we have counts for

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Showing 2024 · cs.CVShow all

5 papers · 2 filters

cs.CV2024★ 1 cited

LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion

Guoliang You, Xiaomeng Chu, Yifan Duan +4

Multi-modal systems enhance performance in autonomous driving but face inefficiencies due to indiscriminate processing within each modality. Additionally, the independent feature l…

cs.CV2024

Perception Helps Planning: Facilitating Multi-Stage Lane-Level Integration via Double-Edge Structures

Guoliang You, Xiaomeng Chu, Yifan Duan +6

When planning for autonomous driving, it is crucial to consider essential traffic elements such as lanes, intersections, traffic regulations, and dynamic agents. However, they are…

cs.CV2024

Agent3D-Zero: An Agent for Zero-shot 3D Understanding

Sha Zhang, Di Huang, Jiajun Deng +4

The ability to understand and reason the 3D real world is a crucial milestone towards artificial general intelligence. The current common practice is to finetune Large Language Mod…

cs.CV2024

HVDistill: Transferring Knowledge from Images to Point Clouds via Unsupervised Hybrid-View Distillation

Sha Zhang, Jiajun Deng, Lei Bai +3

We present a hybrid-view-based knowledge distillation framework, termed HVDistill, to guide the feature learning of a point cloud neural network with a pre-trained image network in…

cs.CV2024★ 3 cited

PoIFusion: Multi-Modal 3D Object Detection via Fusion at Points of Interest

Jiajun Deng, Sha Zhang, Feras Dayoub +3

In this work, we present PoIFusion, a conceptually simple yet effective multi-modal 3D object detection framework to fuse the information of RGB images and LiDAR point clouds at th…