{"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/sparse-voxels-rasterization-real-time-high","title":"Sparse Voxels Rasterization: Real-time High-fidelity Radiance Field Rendering","arxiv_id":"2412.04459","date":"2024-12-05","proceeding":"CVPR 2025 1","authors":["Cheng Sun","Jaesung Choe","Charles Loop","Wei-Chiu Ma","Yu-Chiang Frank Wang"],"abstract":"We propose an efficient radiance field rendering algorithm that incorporates a rasterization process on adaptive sparse voxels without neural networks or 3D Gaussians. There are two key contributions coupled with the proposed system. The first is to adaptively and explicitly allocate sparse voxels to different levels of detail within scenes, faithfully reproducing scene details with $65536^3$ grid resolution while achieving high rendering frame rates. Second, we customize a rasterizer for efficient adaptive sparse voxels rendering. We render voxels in the correct depth order by using ray direction-dependent Morton ordering, which avoids the well-known popping artifact found in Gaussian splatting. Our method improves the previous neural-free voxel model by over 4db PSNR and more than 10x FPS speedup, achieving state-of-the-art comparable novel-view synthesis results. Additionally, our voxel representation is seamlessly compatible with grid-based 3D processing techniques such as Volume Fusion, Voxel Pooling, and Marching Cubes, enabling a wide range of future extensions and applications.","url_abs":"https://arxiv.org/abs/2412.04459v3","url_pdf":"https://arxiv.org/pdf/2412.04459v3.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":"sparse-voxels-rasterization-real-time-high","repo_url":"https://github.com/nvlabs/svraster","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"novel-view-synthesis","task_name":"Novel View Synthesis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2412.04459","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.04459"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+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/nvlabs/svraster","reach":{"status":"ok","spdx":"NOASSERTION"}}],"summary":{"unverified":7},"by_repo_kind":{"official":{"samples":7,"ran":0,"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":7,"samples":[{"code_sha256_prefix":"c471cc571e60c4d9","entry":"compute_rd","repo":"nvlabs/svraster","repo_kind":"official","path":"cuda/svraster_cuda/utils.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/cuda/svraster_cuda/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"c471cc571e60c4d9"}},{"code_sha256_prefix":"06bb25a13f58d6d3","entry":"everytype2bool","repo":"nvlabs/svraster","repo_kind":"official","path":"src/config.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/src/config.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"06bb25a13f58d6d3"}},{"code_sha256_prefix":"8785e2734fd5259d","entry":"is_in_cone","repo":"nvlabs/svraster","repo_kind":"official","path":"cuda/svraster_cuda/utils.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/cuda/svraster_cuda/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"8785e2734fd5259d"}},{"code_sha256_prefix":"a17a82977defa979","entry":"mark_max_samp_rate","repo":"nvlabs/svraster","repo_kind":"official","path":"cuda/svraster_cuda/renderer.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/cuda/svraster_cuda/renderer.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"a17a82977defa979"}},{"code_sha256_prefix":"ede5986f78904323","entry":"mark_n_duplicates","repo":"nvlabs/svraster","repo_kind":"official","path":"cuda/svraster_cuda/renderer.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/cuda/svraster_cuda/renderer.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"ede5986f78904323"}},{"code_sha256_prefix":"c68630475fe28442","entry":"rasterize_voxels","repo":"nvlabs/svraster","repo_kind":"official","path":"cuda/svraster_cuda/renderer.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/cuda/svraster_cuda/renderer.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"c68630475fe28442"}},{"code_sha256_prefix":"0f2bca4bbb15cc6d","entry":"voxel_order_rank","repo":"nvlabs/svraster","repo_kind":"official","path":"cuda/svraster_cuda/utils.py","file_url":"https://github.com/nvlabs/svraster/blob/HEAD/cuda/svraster_cuda/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"0f2bca4bbb15cc6d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}