Search Results for author: Yulu Gao

Found 5 papers, 2 papers with code

Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe

2 code implementations12 Sep 2022 Hongyang Li, Chonghao Sima, Jifeng Dai, Wenhai Wang, Lewei Lu, Huijie Wang, Jia Zeng, Zhiqi Li, Jiazhi Yang, Hanming Deng, Hao Tian, Enze Xie, Jiangwei Xie, Li Chen, Tianyu Li, Yang Li, Yulu Gao, Xiaosong Jia, Si Liu, Jianping Shi, Dahua Lin, Yu Qiao

As sensor configurations get more complex, integrating multi-source information from different sensors and representing features in a unified view come of vital importance.

Autonomous Driving

DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving

1 code implementation ICCV 2023 Xiaosong Jia, Yulu Gao, Li Chen, Junchi Yan, Patrick Langechuan Liu, Hongyang Li

We find that even equipped with a SOTA perception model, directly letting the student model learn the required inputs of the teacher model leads to poor driving performance, which comes from the large distribution gap between predicted privileged inputs and the ground-truth.

Autonomous Driving CARLA longest6

Human-centric Relation Segmentation: Dataset and Solution

no code implementations24 May 2021 Si Liu, Zitian Wang, Yulu Gao, Lejian Ren, Yue Liao, Guanghui Ren, Bo Li, Shuicheng Yan

For the above exemplar case, our HRS task produces results in the form of relation triplets <girl [left hand], hold, book> and exacts segmentation masks of the book, with which the robot can easily accomplish the grabbing task.

Relation Segmentation

Sparse Dense Fusion for 3D Object Detection

no code implementations9 Apr 2023 Yulu Gao, Chonghao Sima, Shaoshuai Shi, Shangzhe Di, Si Liu, Hongyang Li

With the prevalence of multimodal learning, camera-LiDAR fusion has gained popularity in 3D object detection.

3D Object Detection Object +1

Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation

no code implementations12 Dec 2023 Yuanbin Wang, Shaofei Huang, Yulu Gao, Zhen Wang, Rui Wang, Kehua Sheng, Bo Zhang, Si Liu

In this work, we focus on zero-shot point cloud semantic segmentation and propose a simple yet effective baseline to transfer the visual-linguistic knowledge implied in CLIP to point cloud encoder at both feature and output levels.

3D Semantic Segmentation Point Cloud Segmentation +2

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