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arxiv: 2603.19857 · v2 · submitted 2026-03-20 · 💻 cs.SD · cs.CV

Recognition: 1 theorem link

· Lean Theorem

FoleyDirector: Fine-Grained Temporal Steering for Video-to-Audio Generation via Structured Scripts

You Li , Dewei Zhou , Fan Ma , Fu Li , Dongliang He , Yi Yang
Authors on Pith no claims yet

Pith reviewed 2026-05-15 07:31 UTC · model grok-4.3

classification 💻 cs.SD cs.CV
keywords video-to-audio generationtemporal controlstructured scriptsDiT diffusionsound synthesisfoley audiomulti-event audiomultimodal generation
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The pith

FoleyDirector adds structured temporal scripts to DiT-based video-to-audio models for exact timing control over multiple events.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

FoleyDirector targets the lack of fine timing control in video-to-audio generation, where models often fail to place sounds correctly in multi-event scenes or when visuals are unclear. It supplies short-segment captions called Structured Temporal Scripts and fuses them into the diffusion transformer process through a dedicated attention module. This keeps the original audio quality intact while letting users toggle between free generation and scripted control. The approach also adds parallel handling for sounds inside and outside the frame. The result is a practical way for users to direct sound placement as if editing a film soundtrack.

Core claim

FoleyDirector enables precise temporal guidance in DiT-based V2A generation by introducing Structured Temporal Scripts that supply captions for short temporal segments, integrated through the Script-Guided Temporal Fusion Module using Temporal Script Attention, and supported by Bi-Frame Sound Synthesis for multi-event cases, while preserving base-model audio quality and permitting seamless mode switching.

What carries the argument

Script-Guided Temporal Fusion Module, which applies Temporal Script Attention to merge features from Structured Temporal Scripts into the generation pipeline without degrading fidelity.

If this is right

  • Creators gain direct control over when each sound begins and ends in complex scenes.
  • Off-screen and occluded sounds become reliably placeable without relying on visible cues.
  • The same model can produce both free and temporally directed audio tracks interchangeably.
  • New evaluation sets allow direct measurement of timing accuracy in addition to audio realism.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The script format could transfer to other time-aligned generation tasks such as video editing or animation sound design.
  • Extending the scripts to include intensity or spatial cues might further increase controllability beyond timing alone.
  • If the fusion approach generalizes, similar steering could apply to text-to-audio or image-to-audio pipelines.

Load-bearing premise

The fusion module can incorporate the structured scripts without creating audible artifacts or lowering quality when videos contain many overlapping events or weak visual cues.

What would settle it

Generate audio from a multi-event video with scripted timings; if the output either mismatches the requested timing sequence or shows clear quality loss relative to the uncontrolled baseline model, the central claim fails.

Figures

Figures reproduced from arXiv: 2603.19857 by Dewei Zhou, Dongliang He, Fan Ma, Fu Li, Yi Yang, You Li.

Figure 1
Figure 1. Figure 1: FoleyDirector enables (a) temporal control of sound events, (b) supplemental cues when visual information is insufficient, and (c) robust handling of complex multi-event sound rendering. Abstract Recent Video-to-Audio (V2A) methods have achieved re￾markable progress, enabling the synthesis of realistic, high￾quality audio. However, they struggle with fine-grained temporal control in multi-event scenarios o… view at source ↗
Figure 2
Figure 2. Figure 2: Overview of our method. (a) Extraction pipeline of segment-level STS features. (b) Structure of the SG-TFM module, where Temporal Script Attention introduces control signals. (c) Bi-Frame Sound Synthesis Framework, which leverages the controllability of our method in T2A and V2A to enable parallel rendering of in-frame and out-of-frame sounds. Fused block represents the single-modal transformer block in MM… view at source ↗
Figure 3
Figure 3. Figure 3: Qualitative comparison. We visualize the spectrograms of generated audio (by prior works and our method) and the ground￾truth. The curves in the figure represent the recognition confidence for the corresponding sound categories, while the rectangular regions along the curves indicate the time intervals where our fine-grained scripts provide control. performance); b) Usability (shorter durations require mor… view at source ↗
Figure 4
Figure 4. Figure 4: Ablation on training iterations. We show the model metrics after training for different numbers of iterations. The met￾rics are normalized to the range of 0.3–0.8, with higher values indicating better performance. A. Model Architecture DiT Architecture. Our model architecture is designed fol￾lowing the framework of MMAudio, consisting of stacked multi-stream and single-stream DiT blocks. The video input (8… view at source ↗
Figure 5
Figure 5. Figure 5: System Prompt. The system prompt we used in annotation pipeline Distribution matching Quality Semantic Temporal Params FDVGG ↓ FDPANN ↓ FDPaSST↓ KLPANN↓ KLPaSST↓ ISCPANN↑ IB↑ DeSync↓ Medium 621M 1.45 8.23 92.80 1.67 1.47 14.38 0.32 0.439 Large 1.03B 1.47 8.22 93.77 1.66 1.46 14.41 0.32 0.456 Model [PITH_FULL_IMAGE:figures/full_fig_p013_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Visual Results in DirectorBench. We present several results from DirectorBench. E. Benchmark Details In this section, we present the details of the benchmark we constructed. The benchmarks used in our evaluation include DirectorBench and VGGSound-Director. DirectorBench. DirectorBench primarily evaluates a model’s controllability. To build this benchmark, we col￾lected videos from the VGGSound test set and… view at source ↗
Figure 7
Figure 7. Figure 7: Different Architecture. We present the architectural diagrams of different design variants of SG-TFM. (a) concatenates the STS token with features from other modalities; (b) first fuses the STS token with video features using a Fuse-Attention layer; (c) combines the previous two approaches; and (d) shows the design we currently adopt. egories, and overlay the Grounding model’s confidence for the temporal l… view at source ↗
Figure 8
Figure 8. Figure 8: Visual Results in VGGSound-Director. We present several results from VGGSound-Director, comparing the mel-spectrograms generated by our method with those from other approaches and with the ground-truth audio. We also compute the L1 similarity between each generated mel-spectrogram and the ground truth. tention layer fuses STS with the already fused audio fea￾tures. The experimental results are shown in the… view at source ↗
Figure 9
Figure 9. Figure 9: Visual Results in DirectorBench. We present several results from DirectorBench. 5 [PITH_FULL_IMAGE:figures/full_fig_p016_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Visual Results in VGGSound-Director. We present several results from VGGSound-Director, comparing the mel-spectrograms generated by our method with those from other approaches and with the ground-truth audio. We also compute the L1 similarity between each generated mel-spectrogram and the ground truth. The Impact of Bi-Frame. We also visualized the results of the Bi-Frame framework. It can be observed tha… view at source ↗
Figure 11
Figure 11. Figure 11: Visual Results in VGGSound-Director. We present several results from VGGSound-Director, comparing the mel-spectrograms generated by our method with those from other approaches and with the ground-truth audio. We also compute the L1 similarity between each generated mel-spectrogram and the ground truth. Arch FDVGG ↓ KLPANN↓ ISCPANN↑ IB↑ DeSync↓ Concat 1.29 1.26 14.62 0.33 0.476 Attn 1.74 1.54 15.49 0.32 0.… view at source ↗
read the original abstract

Recent Video-to-Audio (V2A) methods have achieved remarkable progress, enabling the synthesis of realistic, high-quality audio. However, they struggle with fine-grained temporal control in multi-event scenarios or when visual cues are insufficient, such as small regions, off-screen sounds, or occluded or partially visible objects. In this paper, we propose FoleyDirector, a framework that, for the first time, enables precise temporal guidance in DiT-based V2A generation while preserving the base model's audio quality and allowing seamless switching between V2A generation and temporally controlled synthesis. FoleyDirector introduces Structured Temporal Scripts (STS), a set of captions corresponding to short temporal segments, to provide richer temporal information. These features are integrated via the Script-Guided Temporal Fusion Module, which employs Temporal Script Attention to fuse STS features coherently. To handle complex multi-event scenarios, we further propose Bi-Frame Sound Synthesis, enabling parallel in-frame and out-of-frame audio generation and improving controllability. To support training and evaluation, we construct the DirectorSound dataset and introduce VGGSoundDirector and DirectorBench. Experiments demonstrate that FoleyDirector substantially enhances temporal controllability while maintaining high audio fidelity, empowering users to act as Foley directors and advancing V2A toward more expressive and controllable generation.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper proposes FoleyDirector, a DiT-based video-to-audio (V2A) framework that introduces Structured Temporal Scripts (STS) as per-segment captions to enable fine-grained temporal control. These are fused via the Script-Guided Temporal Fusion Module using Temporal Script Attention, while Bi-Frame Sound Synthesis generates parallel in-frame and out-of-frame audio for multi-event cases. New resources DirectorSound, VGGSoundDirector, and DirectorBench are presented for training and evaluation. The central claim is that the method delivers precise temporal guidance while preserving base-model audio quality and permitting seamless switching between standard V2A and controlled synthesis.

Significance. If the quantitative claims hold, the work would meaningfully advance controllable V2A by addressing a recognized gap in multi-event and low-visibility scenarios. The modular STS representation and switchable architecture could enable practical user-directed Foley workflows, and the introduced benchmarks would provide a standardized testbed for future temporal-control research.

major comments (3)
  1. [§3.2] §3.2 (Script-Guided Temporal Fusion Module): the Temporal Script Attention mechanism is described only at a high level; without the explicit attention formulation or integration equations, it is impossible to verify that STS features are fused without introducing artifacts or altering the base DiT distribution in low-visibility or occluded-object cases, which is load-bearing for the 'no quality degradation' claim.
  2. [§4.2] §4.2 and Table 3 (Bi-Frame Sound Synthesis ablation): the parallel in-frame/out-of-frame generation is presented as key to multi-event controllability, yet no ablation isolating its contribution versus the fusion module alone is reported; this leaves the attribution of improved temporal metrics on DirectorBench ambiguous.
  3. [§4.3] §4.3 (quantitative results): the abstract asserts 'substantially enhances temporal controllability while maintaining high audio fidelity,' but the visible results lack direct side-by-side comparison of perceptual quality metrics (e.g., FAD, CLAP) against the unmodified DiT baseline on the same multi-event subsets, undermining the preservation claim.
minor comments (2)
  1. [Abstract] The term 'Foley directors' is introduced in the abstract without a brief operational definition; a short clarification in §1 would improve accessibility.
  2. [Figure 2] Figure captions for the architecture diagram should explicitly label the data flow between STS, the fusion module, and the Bi-Frame synthesizer to match the textual description.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive feedback on our manuscript. We address each major comment point by point below and will revise the paper to incorporate the suggested clarifications and additional analyses.

read point-by-point responses

  1. Referee: [§3.2] §3.2 (Script-Guided Temporal Fusion Module): the Temporal Script Attention mechanism is described only at a high level; without the explicit attention formulation or integration equations, it is impossible to verify that STS features are fused without introducing artifacts or altering the base DiT distribution in low-visibility or occluded-object cases, which is load-bearing for the 'no quality degradation' claim.

    Authors: We agree that the description of the Temporal Script Attention in §3.2 is high-level. In the revised manuscript we will add the explicit mathematical formulation, including the query-key-value projections, attention computation, and the precise integration equations showing how STS features are fused into the DiT blocks. These additions will demonstrate that the fusion is designed to preserve the base DiT distribution and does not introduce artifacts, directly supporting the no-degradation claim even in low-visibility and occluded cases. revision: yes

  2. Referee: [§4.2] §4.2 and Table 3 (Bi-Frame Sound Synthesis ablation): the parallel in-frame/out-of-frame generation is presented as key to multi-event controllability, yet no ablation isolating its contribution versus the fusion module alone is reported; this leaves the attribution of improved temporal metrics on DirectorBench ambiguous.

    Authors: The referee is correct that Table 3 does not isolate the Bi-Frame Sound Synthesis contribution from the fusion module. We will add a dedicated ablation in the revised version that fixes the Script-Guided Temporal Fusion Module and compares variants with and without Bi-Frame Sound Synthesis. This will clarify the specific contribution of the parallel in-frame/out-of-frame generation to the temporal metrics on DirectorBench. revision: yes

  3. Referee: [§4.3] §4.3 (quantitative results): the abstract asserts 'substantially enhances temporal controllability while maintaining high audio fidelity,' but the visible results lack direct side-by-side comparison of perceptual quality metrics (e.g., FAD, CLAP) against the unmodified DiT baseline on the same multi-event subsets, undermining the preservation claim.

    Authors: We acknowledge that the current quantitative results do not include direct side-by-side perceptual quality comparisons (FAD, CLAP) of the full model versus the unmodified DiT baseline specifically on multi-event subsets. In the revision we will add these comparisons on the relevant DirectorBench multi-event subsets to provide direct evidence that audio fidelity is preserved. revision: yes

Circularity Check

0 steps flagged

No significant circularity; architectural additions are independent of inputs

full rationale

The paper introduces FoleyDirector as a modular extension to existing DiT-based V2A models via new components (Structured Temporal Scripts, Script-Guided Temporal Fusion Module with Temporal Script Attention, and Bi-Frame Sound Synthesis) plus supporting datasets (DirectorSound, VGGSoundDirector, DirectorBench). No equations, fitted parameters, or self-citations are presented that reduce any claimed result to its own inputs by construction. The temporal control claims rest on the explicit design of these modules rather than any re-derivation or renaming of prior quantities, leaving the derivation self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract provides no explicit free parameters, axioms, or invented entities; the framework appears to rest on standard DiT diffusion assumptions plus the new script representation.

pith-pipeline@v0.9.0 · 5538 in / 1017 out tokens · 32188 ms · 2026-05-15T07:31:39.630696+00:00 · methodology

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