{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/spiking-pointnet-spiking-neural-networks-for-1","title":"Spiking PointNet: Spiking Neural Networks for Point Clouds","arxiv_id":"2310.06232","date":"2023-10-10","proceeding":"NeurIPS 2023 11","authors":["Dayong Ren","Zhe Ma","Yuanpei Chen","Weihang Peng","Xiaode Liu","Yuhan Zhang","Yufei Guo"],"abstract":"Recently, Spiking Neural Networks (SNNs), enjoying extreme energy efficiency, have drawn much research attention on 2D visual recognition and shown gradually increasing application potential. However, it still remains underexplored whether SNNs can be generalized to 3D recognition. To this end, we present Spiking PointNet in the paper, the first spiking neural model for efficient deep learning on point clouds. We discover that the two huge obstacles limiting the application of SNNs in point clouds are: the intrinsic optimization obstacle of SNNs that impedes the training of a big spiking model with large time steps, and the expensive memory and computation cost of PointNet that makes training a big spiking point model unrealistic. To solve the problems simultaneously, we present a trained-less but learning-more paradigm for Spiking PointNet with theoretical justifications and in-depth experimental analysis. In specific, our Spiking PointNet is trained with only a single time step but can obtain better performance with multiple time steps inference, compared to the one trained directly with multiple time steps. We conduct various experiments on ModelNet10, ModelNet40 to demonstrate the effectiveness of Spiking PointNet. Notably, our Spiking PointNet even can outperform its ANN counterpart, which is rare in the SNN field thus providing a potential research direction for the following work. Moreover, Spiking PointNet shows impressive speedup and storage saving in the training phase.","url_abs":"https://arxiv.org/abs/2310.06232v1","url_pdf":"https://arxiv.org/pdf/2310.06232v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"spiking-pointnet-spiking-neural-networks-for-1","repo_url":"https://github.com/dayongren/spiking-pointnet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[{"method_slug":"snn","method_name":"SNN"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2310.06232","atlas_url":"https://app.syntology.ai/?focus=2310.06232","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.06232"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/dayongren/spiking-pointnet","reach":null}],"summary":{"ran":5,"ran_draft_wrong":2,"unverified":3},"by_repo_kind":{"official":{"samples":9,"ran":7,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"53e8918bc52236f1","entry":"LIFAct","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"53e8918bc52236f1"}},{"code_sha256_prefix":"e7008a5cae4666f4","entry":"SpikeBatchNorm","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e7008a5cae4666f4"}},{"code_sha256_prefix":"1e7782123767ff49","entry":"SpikeConv","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1e7782123767ff49"}},{"code_sha256_prefix":"58daf7e76a59d9df","entry":"SpikeLinear","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"58daf7e76a59d9df"}},{"code_sha256_prefix":"c494ea8e2c450547","entry":"SpikeModel","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c494ea8e2c450547"}},{"code_sha256_prefix":"3feff0fd15c37746","entry":"mem_update","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3feff0fd15c37746"}},{"code_sha256_prefix":"cbe6b782dd0724b0","entry":"spike_activation","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"cbe6b782dd0724b0"}},{"code_sha256_prefix":"4a02254778236267","entry":"SpikeModule","repo":"dayongren/spiking-pointnet","repo_kind":"official","path":"models/spike_model.py","file_url":"https://github.com/dayongren/spiking-pointnet/blob/HEAD/models/spike_model.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"4a02254778236267"}},{"code_sha256_prefix":"290bbfb3d5c4811c","entry":"test","repo":"DayongRen/Spiking-PointNet","repo_kind":"official","path":"test_classification.py","file_url":"https://github.com/DayongRen/Spiking-PointNet/blob/HEAD/test_classification.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"290bbfb3d5c4811c"}},{"code_sha256_prefix":"cce988c817575a1a","entry":"test","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"cce988c817575a1a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}