AI Paper Atlas

Research map / Detection and segmentation / Open-set and few-shot detection

RealImpact: A Dataset of Impact Sound Fields for Real Objects

CVPR 2023 · Detection and segmentation › Open-set and few-shot detection · approach: Object-level representation learning · 10 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use explicit acoustic-transfer modeling rather than modeling structural vibration aloneObject impact sound simulation · RealImpact Deconvolved and Deconvolved + DenoisedL1 Spectral: KleinPat 0.747 -> 0.632; NeuralSound 0.747 -> 0.673; denoised: KleinPat 0.236 -> 0.0982; NeuralSound 0.236 -> 0.133Helped
Use explicit acoustic-transfer modeling rather than modeling structural vibration aloneObject impact sound simulation · RealImpact Deconvolved and Deconvolved + DenoisedCDPAM: KleinPat 0.297 -> 0.117; NeuralSound 0.297 -> 0.102; denoised: KleinPat 0.289 -> 0.0975; NeuralSound 0.289 -> 0.0750Helped
Compare against denoised rather than raw deconvolved recordingsSimulation baseline evaluation · RealImpact recordingsL1 Spectral: Random Impact Sound 0.728 -> 0.150; KleinPat 0.632 -> 0.0982; NeuralSound 0.673 -> 0.133; ObjectFolder 2.0 0.747 -> 0.23Helped
Compare against denoised rather than raw deconvolved recordingsSimulation baseline evaluation · RealImpact recordingsEnvelope (× 10^-3): Random Impact Sound 4.17 -> 4.97; KleinPat 4.63 -> 4.63; NeuralSound 23.0 -> 22.8; ObjectFolder 2.0 25.6 -> 25.4Mixed
Compare against denoised rather than raw deconvolved recordingsSimulation baseline evaluation · RealImpact recordingsCDPAM: Random Impact Sound 0.121 -> 0.0880; KleinPat 0.117 -> 0.0975; NeuralSound 0.102 -> 0.0750; ObjectFolder 2.0 0.297 -> 0.Helped
Use a random impact recording instead of a simulationObject impact sound comparison · RealImpact DeconvolvedEnvelope (× 10^-3): 4.63 -> 4.17Helped
Use a random impact recording instead of a simulationObject impact sound comparison · RealImpact Deconvolved + DenoisedEnvelope (× 10^-3): 4.63 -> 4.97Hurt
Predict listener position from the impact soundRealImpact listener location classification · Angle, height, and distanceAccuracy (%): 10.0 -> 57.9; 6.7 -> 60.7; 25.0 -> 67.4Helped
Match impact recordings to corresponding RGB imagesRealImpact visual acoustic matching · Visual Acoustic MatchingAccuracy (%): 50.0 -> 75.1Helped
Match impact recordings to corresponding RGB imagesRealImpact visual acoustic matching · Visual Acoustic MatchingRMSE angle error (degrees): 59.7 -> 47.7Helped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy