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CategoriesTasksDatasets# of samplesDomain
Image + TextImage-→Text,Text-→Image Text-→Image+TextLaion400M [42]400MOpen
Audio + TextText→Audio,Audio-→Text, Text-→Audio+Text,Audio-Text CTAudioSet [16] AudioCaps [24] Freesound 500K BBC Sound Effect900K* 46K 2.5M 30KYouTube YouTube Public audio samples Authentic natural sound
AudiovisualImage→Audio,Image→Video+AudioAudioSet SoundNet [3]900K* 1.0M*YouTube Flickr, natural sound
VideoText-→Video,Image→Video, Video-Text CTWebvid10M[4] HD-Villa-100M [54]10.7M 100MShort videos YouTube
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ModelDatasetsFD↓IS个KL←FAD↓OVL ↑REL个
Ground truth-----83.6180.11
DiffSoundAS+AC47.684.012.527.7545.0043.83
AudioGenAS +AC+8others=-2.093.13-=
AudioLDM-L-FullAS+AC+FSD+BBC23.318.131.591.9665.9165.97
CoDi(Ours)AS+AC+FSD+BBC+SDN22.908.771.401.8066.8767.60
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ModelSPIDErCIDErSPICE
AudioCaps [24]0.3690.5930.144
BART-Finetune [17]0.4650.7530.176
VALOR[7]0.741
AL-MixGen [25]0.4660.7550.177
CoDi (Ours)0.4800.7890.182
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ModelB@4METEORCIDEr
ORG-TRL[58]43.628.850.9
MV-GPT[43]48.938.760.0
GIT[48]54.833.175.9
mPLUG-2 [52]57.834.980.3
CoDi(Ours)52.132.574.4
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ModelB@4METEORCIDEr
Autoregressive Model
Oscar [31]36.5830.4124.12
ClipCap [35]32.1527.1108.35
OFA [49]44.932.5154.9
BLIP2 [30]43.7-145.8
Diffusion Model
DDCap [59]35.028.2117.8
SCD-Net [34]39.429.2131.6
CoDi (Ours)40.231.0149.9
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MethodZero-ShotCLIPSIM ↑
GODIVA [50]No0.2402
NUWA [51]No0.2439
CogVideo [22]Yes0.2631
Make-A-Video [44]Yes0.3049
Video LDM[5]Yes0.2929
CoDi(Ours)Yes0.2890
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MethodFID↓
CogView [10]27.10
GLIDE [36]12.24
Make-a-Scene [15]11.84
LDM [41]12.63
Stable Diffusion-1.411.21
Stable Diffusion-1.511.12
Versatile Diffusion [53]11.10
CoDi (Ours)11.26
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MethodIS(1)FVD (↑)
Cog Video (Chinese)23.55751.34
CogVideo (English)25.27701.59
Make-A-Video33.00367.23
Video LDM33.45550.61
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InputsCLIPSIM个
Single-modality Prompt
Text0.2890
Dual-modality Prompt
Text+Audio0.2912
Text+Image0.2891
Text+Audio+Image0.2923
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InputsFID↓
Single-modality Prompt
Text14.2
Audio14.3
Dual-modality Prompt
Text+Audio14.9
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InputsSIM-ITSIM-ATSIM-VTSIM-VA
Two Joint Outputs
Audio → Image+Text0.251 / 0.260
Image→Audio+Text■0.244 / 0.256
Text →Video+Audio0.240 / 0.255
Audio →Video+Text0.256 / 0.261
Three Joint Outputs
Text-→ Video+Image+Audio 0.256/0.270 0.240/0.2570.240 / 0.257
Multi-Inputs-Outputs
Text+Image -→ Video+Audio0.247 / 0.259
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ModalityVideo (Image) LDMAudio LDMText LDM
Hyperparameter
ArchitectureLDMLDMLDM
z-shape4× #frames × 64× 648× 256×16768×1×1
Channels320320320
Depth422
Channel multiplier1,2,4,41,2,4,41,2,4,4
Attention resolutions64,32,1664,32,1664,32,16
Head channels323232
Number of heads888
CA embed dim768768768
CA resolutions64,32,1664,32,1664,32,16
AutoencodersAutoKLAudioLDMOptimus
Weight initializationStable Diffusion-1.4-Versatile Diffusion
ParameterizationEEE
Learning rate2e-55e-65e-5
Total batch size25610241024
Diffusion Setup
Diffusion steps100010001000
Noise scheduleLinearLinearLinear
β0.000850.000850.00085
阳0.01200.01200.0120
Sampling Parameters
SamplerDDIMDDIMDDIM
Steps505050
n1.01.01.0
Guidance scale2.07.52.0
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