Training-free 3D Point Cloud Classification on ModelNet40

Metric: Accuracy (%) (higher is better)

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#	Model↕	Accuracy (%)▼	Extra Data	Paper	Date↕	Code
1	Point-GN	85.3	No	Point-GN: A Non-Parametric Network Using Gaussia...	2024-12-04	Code
2	Point-NN	82.6	No	Parameter is Not All You Need: Starting from Non...	2023-03-14	Code
3	PointCLIP V2	64.2	Yes	PointCLIP V2: Prompting CLIP and GPT for Powerfu...	2022-11-21	Code
4	ULIP	60.4	Yes	ULIP: Learning a Unified Representation of Langu...	2022-12-10	Code
5	CLIP2Point	49.4	Yes	CLIP2Point: Transfer CLIP to Point Cloud Classif...	2022-10-03	Code
6	CALIP	21.5	Yes	CALIP: Zero-Shot Enhancement of CLIP with Parame...	2022-09-28	Code
7	PointCLIP	20.2	Yes	PointCLIP: Point Cloud Understanding by CLIP	2021-12-04	Code

#1Point-GNSOTA
85.3
Accuracy (%)· 2024-12-04
Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud Classification Code
#2Point-NNSOTA
82.6
Accuracy (%)· 2023-03-14
Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis Code
#3PointCLIP V2SOTA
64.2
Accuracy (%)· Extra Data· 2022-11-21
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning Code
#4ULIP
60.4
Accuracy (%)· Extra Data· 2022-12-10
ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding Code
#5CLIP2PointSOTA
49.4
Accuracy (%)· Extra Data· 2022-10-03
CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training Code
#6CALIPSOTA
21.5
Accuracy (%)· Extra Data· 2022-09-28
CALIP: Zero-Shot Enhancement of CLIP with Parameter-free Attention Code
#7PointCLIPSOTA
20.2
Accuracy (%)· Extra Data· 2021-12-04
PointCLIP: Point Cloud Understanding by CLIP Code