LidarCLIP or: How I Learned to Talk to Point Clouds
Paper i proceeding, 2024

Research connecting text and images has recently seen several breakthroughs, with models like CLIP, DALL•E 2, and Stable Diffusion. However, the connection between text and other visual modalities, such as lidar data, has received less attention, prohibited by the lack of text-lidar datasets. In this work, we propose LidarCLIP, a mapping from automotive point clouds to a pre-existing CLIP embedding space. Using image-lidar pairs, we supervise a point cloud encoder with the image CLIP embeddings, effectively relating text and lidar data with the image domain as an intermediary. We show the effectiveness of Lidar-CLIP by demonstrating that lidar-based retrieval is generally on par with image-based retrieval, but with complementary strengths and weaknesses. By combining image and lidar features, we improve upon both single-modality methods and enable a targeted search for challenging detection scenarios under adverse sensor conditions. We also explore zero-shot classification and show that LidarCLIP outperforms existing attempts to use CLIP for point clouds by a large margin. Finally, we leverage our compatibility with CLIP to explore a range of applications, such as point cloud captioning and lidar-to-image generation, without any additional training. Code and pre-trained models at

autonoma fordon

autonomous driving

point clouds




Georg Hess

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Adam Tonderski

Zenseact AB

Christoffer Petersson

Chalmers, Matematiska vetenskaper, Algebra och geometri

Kalle Åström

Lunds universitet

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Proceedings of the 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

2642-9381 (ISSN)

979-8-3503-1892-0 (ISBN)

2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024
Waikoloa, USA,

Målföljning och djup maskininlärning för trajektorieskattning med tillämpning mot noggranna referenssystem

VINNOVA (2017-05521), 2018-07-01 -- 2022-06-30.




Datorseende och robotik (autonoma system)



Mer information

Senast uppdaterat