{"id":"ceb51b45-9c2a-45a8-bce8-df9f06e95910","arxiv_id":"2508.05343","paper_version":1,"verdict":"UNVERDICTED","confidence":"LOW","novelty_score":6.0,"correctness_risk":"unknown","formal_verification":"none","parameter_count":4,"one_line_summary":"A Gabor-based primitive, a weighted bank of Gaussian and Gabor kernels with learnable 3D frequencies, replaces the standard Gaussian kernel in 3D Gaussian Splatting for novel view rendering.","lead":"This paper swaps the smooth Gaussian blobs used in 3D scene rendering for wavy Gabor kernels that can be tuned to specific directions and frequencies, and adds a custom renderer. The authors report sharper images with fewer stored primitives, but the reviewed manuscript omits the experiments needed to verify that gain.","discovery_kind":"new_method","skeptic_critique":{"model":"deepseek-v4-flash","headline":"Supplementary A.2 omits the z-integration result; the effective 2D Gabor frequency is shifted by -(A02/A22)f_z, -(A12/A22)f_z. If the rasterizer uses only the xy part of f_proj, every tilted off-axis Gabor splat is rendered at the wrong modulation frequency.","rationale":"The reader's weakest-assumption analysis focused on the local-affine approximation in Eq. (16). I agree that the affine projection of frequencies is fragile for high-frequency Gabor kernels, but I identify a more concrete and checkable gap: the supplementary derivation of the 3D-to-2D integration is incomplete, and completing it reveals a frequency shift that depends on the off-diagonal covariance terms. If the rasterizer ignores this shift, the rendered splat is not the projection of the intended 3D Gabor, so the central quality claim fails regardless of the affine approximation accuracy. This is a genuine mathematical vulnerability, but the manuscript as provided is too incomplete to confirm that the implementation errs; it may be that the missing pages contain the correct final formula and rasterizer logic. The paper also has no experimental section, so the empirical 1.35 dB claim remains unverifiable. Given these gaps, the reader's UNVERDICTED verdict is appropriate, and my concern does not change it: it sharpens the reason why verification is needed rather than moving the verdict to ACCEPT or REJECT.","tokens_in":12710,"tokens_out":6059,"duration_ms":64227,"concrete_test":"Independently complete the z-integration in Supplementary A.2 and derive the effective 2D frequency f_eff = (f_x - A02/A22 f_z, f_y - A12/A22 f_z), where A = (Σ'')^{-1}. Then instrument or simulate the proposed CUDA rasterizer with a single tilted Gabor primitive having nonzero off-diagonal covariance and f_z ≠ 0. Compare the rendered 2D splat against a brute-force numerical projection (ray-marched integration of the 3D Gabor along z). If the rendered splat's phase corresponds to f_eff, the concern is resolved; if it corresponds to the unshifted (f_x, f_y), the rasterizer is inconsistent with the stated 3D primitive and the high-frequency reconstruction claim is not supported.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The central claim requires that a 3D Gabor kernel, after projection and z-integration, produces the intended 2D Gabor splat. Supplementary Eq. (17) gives the projected 3D frequency as f_proj^T = f^T (JW)^{-1}. But A.2, which is supposed to derive the 3D-to-2D integral, stops at Eq. (23) without stating the final 2D formula. Completing the integral for a kernel exp(-1/2 x^T A x + i2π f·x), with A = (Σ'')^{-1}, shows the resulting 2D phase is i2π[(f_x - A02/A22 f_z)x + (f_y - A12/A22 f_z)y], not i2π(f_x x + f_y y). The shift arises from the coupling between the off-diagonal precision entries and the z-component of the projected frequency. Unless the rasterizer explicitly accounts for this shift, a tilted, anisotropic Gabor primitive with nonzero f_z, exactly the kind needed for directional high-frequency detail, is projected to a 2D splat whose oscillation frequency differs from the true projection of the 3D kernel. The paper does not show that its CUDA rasterizer implements this correction, and the omitted final formula makes it impossible to verify. This is more specific than the standard local-affine approximation concern: even if the affine Jacobian is exact, the z-integration step itself changes the effective 2D frequency.","agreement_with_reader":"partial"},"referee_report":{"model":"deepseek-v4-flash","summary":"The paper proposes 3DGabSplat, which replaces the 3D Gaussian primitives of 3D Gaussian Splatting with 3D Gabor-based primitives. Each primitive is a weighted sum of a Gaussian kernel and multiple 3D Gabor kernels with distinct 3D frequency vectors, forming a filter bank intended to capture high-frequency and directional details. The authors derive the 3D-to-2D projection of these primitives using the same affine Jacobian approximation as 3DGS, state that the projected Gabor frequency transforms as f_proj^T = f^T (JW)^{-1}, and describe a CUDA rasterizer that integrates the projected 3D kernel along the z-axis. They also outline a frequency-adaptive optimization mechanism. The paper claims state-of-the-art novel view synthesis, including up to 1.35 dB PSNR gain over 3DGS with fewer primitives and lower memory consumption.","tokens_in":13109,"tokens_out":7554,"duration_ms":78213,"significance":"If the claims hold, the paper would make a meaningful contribution: it replaces low-pass Gaussian kernels with band-pass Gabor primitives, a natural extension that could improve high-frequency detail while reducing primitive count. The formulation is not circular: Gabor frequencies and weights are fitted to training views and evaluated on test views. The projection of covariance and frequency in Supplementary Eqs. (16)-(17) is mathematically coherent. However, the central empirical claims are not verifiable in the reviewed text because no experimental section is included, and the z-integration derivation is incomplete in a way that matters for the correctness of the rasterizer. The idea is promising, but the manuscript as provided is not yet reproducible or fully supported.","major_comments":[{"comment":"Eq. (23) stops before the z-integration is completed. For a projected kernel exp(-1/2 x^T A x + i 2π f_proj^T x), the integral over z yields a 2D phase with frequency (f_x - (A02/A22)f_z, f_y - (A12/A22)f_z), not simply the xy part of f_proj. If the CUDA rasterizer uses only the xy components of the projected frequency from Eq. (17), then every tilted Gabor primitive with nonzero f_z is rendered at the wrong modulation frequency. This directly affects the paper's central claim of improved high-frequency reconstruction. The completed 2D Gabor formula must be stated explicitly, and the rasterizer's handling of the A02/A22 and A12/A22 shift must be documented or tested.","section":"Supplementary A.2, Eq. (23)"},{"comment":"The manuscript text provided for review contains no experimental section: no PSNR/SSIM/LPIPS tables, no primitive counts, no memory measurements, and no timing results. The abstract's claims of 'up to 1.35 dB PSNR gain over 3DGS' and 'reduced number of primitives and memory consumption' are therefore unsupported in this version. The empirical section must be present and should report per-scene results, baseline configurations, and standard deviations to support the stated gains.","section":"Experimental evaluation (missing in reviewed text)"},{"comment":"The frequency-adaptive mechanism is described only at a high level: the paper states that frequencies and coefficients are dynamically adjusted during densification and optimization, but no equations, update rules, initialization strategy, or regularization are provided. Since the method's name and claimed benefit depend on this mechanism, the missing algorithmic detail prevents reproducibility and evaluation of whether the adaptivity is essential to the reported gains.","section":"Section 3, frequency-adaptive mechanism"}],"minor_comments":[{"comment":"The supplementary text contains many rendering artifacts (e.g., '/u1D454', '/u1D6BA', 'parenlefttpA'), making the derivation hard to read. The final version should be typeset cleanly.","section":"Throughout supplementary"},{"comment":"The symbol f is used both for the original 3D frequency and, after Eq. (17), for the projected frequency. Please use distinct notation (e.g., f and f_proj) in the z-integration derivation to avoid confusion.","section":"Supplementary A.1/A.2 notation"},{"comment":"The comparison with 2D Gabor splatting [53] would benefit from a precise statement of its 'fixed direction' limitation: does it use a single 1D frequency modulation per kernel, and how does your 3D formulation degenerate to it? This would clarify the claimed novelty.","section":"Section 2.2 / related work"},{"comment":"Please provide a pseudocode or algorithmic listing of the rasterizer, especially the step where the 3D Gabor frequency is converted to the 2D splat. This is needed to verify the z-integration issue raised above.","section":"CUDA rasterizer"},{"comment":"The 'up to 1.35 dB PSNR gain' claim should specify over which scenes and under which configuration; reporting only the maximum can be misleading without the full distribution.","section":"Abstract"}],"recommendation":"major_revision","confidential_remarks":"The provided manuscript text appears to be missing the entire experimental section, which makes a fair assessment of the central empirical claims impossible. If this is an artifact of the review PDF extraction, the authors should be asked to supply the full version. The incomplete z-integration in Supplementary A.2 is a genuine correctness risk that should be resolved before acceptance, because the rasterizer may be rendering tilted Gabor splats at the wrong frequency."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"The core idea is genuinely new and worth taking seriously: replacing 3DGS Gaussian kernels with 3D Gabor primitives forming a filter bank of directional frequencies, then projecting through a 3DGS-style rasterizer. That is a clean representational change, distinct from 2D Gabor splatting and from Gabor activations inside MLPs. The paper also correctly identifies the Gaussian low-pass limitation and makes a plausible case that oscillatory kernels could capture high-frequency detail with fewer primitives. The affine projection derivation in the supplementary (Eq. 16-17) is standard and, so far as it goes, correct: covariance transforms as JW Sigma W^T J^T and frequency as f^T (JW)^{-1}.\n\nThe problems are concrete and load-bearing. First, the manuscript as provided contains no experimental section at all. The abstract claims up to 1.35 dB PSNR gain over 3DGS with fewer primitives and lower memory, but there are no tables, no ablations, no timing numbers, nothing to check. That is not a minor omission; the central empirical claim is unevaluable. There is also no code release, so the claimed CUDA rasterizer cannot be inspected.\n\nSecond, the stress-test note about the z-integration is correct. Supplementary A.2 stops at Eq. (23) without giving the final 2D formula. Completing the Gaussian integral over z for a kernel with frequency f and precision A introduces cross-coupling terms: the effective 2D modulation frequency becomes (f_x - A02/A22 f_z, f_y - A12/A22 f_z), not simply the xy part of the projected 3D frequency. For a tilted, anisotropic Gabor splat with nonzero f_z, using only (f_x, f_y) renders the splat at the wrong oscillation frequency. The paper never states this correction, and the frozen rasterizer cannot be checked. This is more than a cosmetic gap: it directly affects whether the claimed high-frequency gains materialize.\n\nThe math is otherwise coherent and not circular. The authors know the relevant literature and position against 2DGabSplat and NeuRBF/WIRE honestly. But the submission is not in a reviewable state: half the method is missing, the empirical evidence is absent, and the derivation stops exactly where the tricky part starts.\n\nWho gets value from this: researchers working on alternative splatting primitives will find the Gabor filter-bank idea suggestive, but they will need the complete version to build on it. My recommendation: if this truncated version is what the editor receives, desk reject with an invitation to resubmit the full paper. If the full paper with experiments exists, send it to a serious referee — the idea deserves scrutiny, and the specific z-integration frequency-shift issue should be resolved before acceptance.","headline":"Novel and plausible 3D Gabor extension of 3DGS, but the submission is incomplete: no experiments are present, and the supplementary derivation omits a z-integration frequency shift that the rasterizer would need to handle.","tokens_in":13643,"tokens_out":1592,"would_cite":false,"duration_ms":19446,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"The paper claims that replacing 3D Gaussian kernels with 3D Gabor filter banks raises novel-view PSNR by up to 1.35 dB while cutting primitive count and memory.","keywords":["3D Gaussian Splatting","Gabor filter","3D Gabor kernels","novel view synthesis","radiance field rendering","frequency-adaptive optimization","real-time rendering","differentiable rasterization"],"falsifier":"Render a synthetic checkerboard or sinusoidal grating with known frequency from a range of distances and incidence angles using 3DGabSplat and 3DGS, and measure PSNR as the affine projection error grows. If the gap narrows to zero, or if the rendered texture shows phase scrambling relative to the expected projected frequency $(JW)^{-\\top}\\mathbf{f}$, the claimed benefit is not real.","tokens_in":12640,"feed_emoji":"🖼️","tokens_out":12218,"duration_ms":117190,"temperature":0.7,"pith_summary":"The paper proposes 3DGabSplat, a variant of 3D Gaussian Splatting in which each primitive is a 3D Gabor filter bank—a Gaussian envelope modulated by several cosine waves at different 3D directions and frequencies—rather than a single low-pass Gaussian. It argues that one such primitive can encode high-frequency texture that 3DGS needs many redundant Gaussians to approximate, and it shows how to project these oscillatory kernels to 2D so real-time rendering is preserved. If the claim is right, novel-view synthesis becomes better and cheaper at the same time: higher fidelity, fewer primitives, and lower memory. The concrete promise is an up to 1.35 dB PSNR gain over 3DGS with simultaneously reduced primitive count and memory consumption.","feed_headline":"3D Gabor splatting beats 3DGS by 1.35 dB with fewer primitives","feed_subtitle":"Replacing Gaussian primitives with 3D Gabor filter banks adds detail and cuts memory in real-time rendering.","key_machinery":"The load-bearing object is the 3D Gabor kernel above, grouped into a per-primitive filter bank: one Gaussian (frequency zero) plus $K$ Gabor kernels with distinct frequency vectors $\\mathbf{f}_k$ and scalar weights. The argument rides on the projection identity $\\mathbf{f}_{\\mathrm{proj}}^\\top = \\mathbf{f}^\\top(JW)^{-1}$: the directional frequency of a 3D kernel transforms under the same affine map that transports the Gaussian covariance, so the high-frequency structure is not averaged away during splatting. The second piece is the z-axis integration of a Gaussian envelope times a cosine, which reduces the 3D bank to a sum of 2D anisotropic Gaussian-windowed sinusoids; that sum is what the r","core_discovery":"Each scene primitive is no longer a single Gaussian; it is a filter bank. A 3D Gabor kernel is $G(\\mathbf{x}) = \\exp\\left(-\\frac{1}{2}(\\mathbf{x}-\\boldsymbol{\\mu})^\\top \\Sigma^{-1}(\\mathbf{x}-\\boldsymbol{\\mu})\\right)\\cos(2\\pi \\mathbf{f}^\\top(\\mathbf{x}-\\boldsymbol{\\mu}))$, a Gaussian envelope modulated by a cosine with its own 3D frequency vector $\\mathbf{f}$ and weight. The primitive sums this bank with a plain Gaussian (the $\\mathbf{f}=0$ limit), so one splat carries low-frequency shape and several directional high-frequency textures. For rendering, the paper shows that the standard 3DGS projection step—world-to-camera $W$ followed by the affine Jacobian $J$—also projects the frequency: $\\","pith_inferences":["Because each primitive carries explicit frequency vectors, a natural extension the paper does not state is analytic level-of-detail: given a pixel footprint, drop or damp Gabor kernels whose projected frequency exceeds the Nyquist limit, yielding principled anti-aliasing.","The affine frequency projection is likely to be the weak point in near-field or grazing-angle views; a synthetic stress test with known sinusoidal textures at varying depth and obliqueness could show whether the 1.35 dB gain persists or collapses exactly there.","The same filter-bank primitive could be dropped into 3DGS-based SLAM, dynamic scenes, or compression pipelines, where fewer primitives would directly reduce memory and per-frame cost; this is an editorial extension, not a paper claim.","Given the Gabor/wavelet lineage in neural fields, the explicit frequencies could be connected to perceptual quality: optimize the bank against frequency bands that matter for human perception, a testable variant not explored here."],"forward_implications":["A single 3DGabSplat primitive can carry a band of frequencies, so fine textures that force 3DGS to stack many overlapping Gaussians can be represented by fewer primitives; hence quality, memory, and training cost improve together.","The kernel is plug-and-play with the existing 3DGS pipeline: only the primitive definition, projection, and rasterizer change, so downstream 3DGS systems can adopt it without redesign.","Because setting all $\\mathbf{f}_k = 0$ recovers a Gaussian, 3DGS is a special case of 3DGabSplat; a single fixed-direction Gabor likewise recovers 2D Gabor splatting, so the method strictly generalizes both.","Real-time rendering survives the added frequency channels: the custom CUDA rasterizer alpha-blends the projected Gabor bank in a single pass.","The frequency-adaptive optimizer automatically allocates high-frequency kernels to texture-rich regions, making bandwidth assignment part of training rather than a manual choice."],"supporting_citations":[{"why":"Supplies the base splatting pipeline, affine Jacobian projection, and rasterization approach that 3DGabSplat modifies for Gabor primitives.","marker":"[25]"},{"why":"Closest prior work: 2D Gabor splatting with fixed 1D frequency modulation, which the paper extends to direction-dependent 3D frequencies.","marker":"[53]"},{"why":"Alternative-primitive baseline (generalized exponential splatting) used in the experimental comparison.","marker":"[17]"},{"why":"Alternative-primitive baseline (3D smooth convexes) used in the experimental comparison.","marker":"[19]"},{"why":"Alternative-primitive baseline (2D Gaussian surfels) used in the experimental comparison.","marker":"[21]"},{"why":"Alternative-primitive baseline (3D half-Gaussian kernels) used in the experimental comparison.","marker":"[31]"},{"why":"Alternative-primitive baseline (deformable Beta kernels) used in the experimental comparison.","marker":"[34]"}],"fun_headline_variants":["3D Gabor splatting tops 3DGS by 1.35 dB with fewer splats","Frequency-adaptive Gabor splats beat Gaussian splats in rendering","Single Gabor splat encodes low-pass base plus directional details","3DGabSplat filter bank splats for SOTA real-time rendering","3D Gabor filter banks fix Gaussian splatting's blurry details"],"cache_read_input_tokens":2816,"weakest_assumption_plain":"The load-bearing premise is that the perspective camera transformation can be treated as a single affine map across the whole footprint of each 3D Gabor kernel; when the cosine oscillates quickly, even a small error in that map displaces the very frequency the kernel was meant to paint.","fun_headline_variants_meta":{"raw":{"variants":["3D Gabor splatting tops 3DGS by 1.35 dB with fewer splats","Frequency-adaptive Gabor splats beat Gaussian splats in rendering","Single Gabor splat encodes low-pass base plus directional details","3DGabSplat filter bank splats for SOTA real-time rendering","3D Gabor filter banks fix Gaussian splatting's blurry details"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000816,"raw_usage":{"total_tokens":3488,"prompt_tokens":893,"completion_tokens":2595,"prompt_tokens_details":{"cached_tokens":256},"prompt_cache_hit_tokens":256,"prompt_cache_miss_tokens":637,"completion_tokens_details":{"reasoning_tokens":2492}},"tokens_in":637,"tokens_out":2595,"duration_ms":20690,"temperature":1.0,"reasoning_tokens":2492,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-05T23:24:06.711820+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Render a synthetic checkerboard or sinusoidal grating with known frequency from a range of distances and incidence angles using 3DGabSplat and 3DGS, and measure PSNR as the affine projection error grows. If the gap narrows to zero, or if the rendered texture shows phase scrambling relative to the expected projected frequency $(JW)^{-\\top}\\mathbf{f}$, the claimed benefit is not real.","supporting_citations":[{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Closest prior work: 2D Gabor splatting with fixed 1D frequency modulation, which the paper extends to direction-dependent 3D frequencies."},{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Alternative-primitive baseline (generalized exponential splatting) used in the experimental comparison."},{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Alternative-primitive baseline (3D smooth convexes) used in the experimental comparison."},{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Alternative-primitive baseline (2D Gaussian surfels) used in the experimental comparison."},{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Alternative-primitive baseline (3D half-Gaussian kernels) used in the experimental comparison."},{"cited_title":"In Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition","cited_arxiv_id":null,"evidence_quote":"Alternative-primitive baseline (deformable Beta kernels) used in the experimental comparison."}],"review_version":1}