arXiv:2510. 01891v2 Announce Type: replace-cross Abstract: Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are crucial for realistic spatial audio rendering.
arXiv:2603. 27998v2 Announce Type: replace-cross Abstract: Individualized head-related impulse responses (HRIRs) enable binaural rendering, but dense per-listener measurements are costly.
arXiv:2610.08760v1 Announce Type: cross Abstract: Recent advances in world models have enabled increasingly realistic visual synthesis. However, these generated environments remain largely silent. Br...
The paper introduces StereoBind, a framework that links visual source motion to stereo audio generation, addressing the need for dynamic spatial correspondence in immersive applications like AR/VR and gaming. It employs three mechanisms—Visual Motion Binding, Spatial Track Encoder, and Residual Track RoPE—to coordinate visual motion with stereo sound. The authors also present StereoWorld-29K, a large-scale dataset with paired motion tracks, and StereoWorldBench for evaluating audiovisual spatial consistency, demonstrating that StereoBind improves spatial alignment while maintaining overall quality.
arXiv:2609.38748v1 Announce Type: new Abstract: Recent joint video-audio generation models have achieved strong semantic correspondence and temporal synchronization. However, applications such as AR/...
arXiv:2609.16664v1 Announce Type: new Abstract: Leveraging Large Vision-Language Models like CLIP has recently set new benchmarks for No-Reference Image Quality Assessment (NR-IQA). However, the cont...
arXiv:2607. 03806v1 Announce Type: cross Abstract: Audio foundation models are widely adopted as general-purpose feature extractors, yet the internal structure of their learned representations remains insufficiently understood.
arXiv:2609.38444v1 Announce Type: new Abstract: Text- and image-conditioned world generators can create visually rich 3D environments, yet these worlds often remain silent or rely on soundtracks synt...
arXiv:2609.38689v1 Announce Type: new Abstract: Immersive displays can enable rich and diverse virtual experiences. Manually authoring every possible experience to realize this potential, however, is...
arXiv:2608. 16285v1 Announce Type: cross Abstract: Audio-Visual Segmentation (AVS) is a fundamental task in multimodal perception that performs pixel-level segmentation of sounding objects in videos by leveraging both visual and audio cues.
SAVU-Bench is a real‑world benchmark designed to evaluate spatial audio‑visual understanding across three capability levels and seven tasks, addressing limitations of prior simulated‑scene datasets. It includes a diagnostic set, SAVU‑Diag, that breaks down reasoning questions into grounding and alignment sub‑tasks, revealing that many errors stem from failures in these prerequisites. A training‑free baseline, SAVU‑EA, improves spatial grounding and joint matching but high‑level reasoning remains difficult, underscoring the need for better audio perception and cross‑modal spatial integration.
Leveraging Large Vision-Language Models like CLIP has recently set new benchmarks for No-Reference Image Quality Assessment (NR-IQA). However, the contrastive pretraining of CLIP inherently prioritize...
PRISM‑Bench is an audio‑centric diagnostic benchmark for text‑to‑audio‑video generation, built from 900 human‑verified samples. It evaluates audio along two axes—audio type (speech, music, sound) and sound‑source visibility (on‑screen vs. off‑screen)—across four perceptual dimensions (audio‑visual coherence, audio quality, audio expressiveness, and prompt following) using 35 fine‑grained criteria. The benchmark employs an enhanced MLLM‑as‑a‑Judge protocol that aligns strongly with human raters, revealing a performance gap between frontier and open‑source T2AV models and highlighting overfitting to perceptual fidelity while struggling with complex grounding and control tasks, especially for music and synchronized on‑screen audio.