Dataset Viewer
Auto-converted to Parquet Duplicate
image
imagewidth (px)
1.22k
1.22k
markdown
stringclasses
1 value
html_source
stringclasses
1 value
id
stringlengths
73
74
layout_detection
listlengths
14
159
reading_order
sequencelengths
0
0
latex_extracted
sequencelengths
6
6
image_caption_pairs
listlengths
13
13
vqa
sequencelengths
0
0
page_number
int64
0
15
image_dim
sequencelengths
2
2
# Retrieval-Augmented Diffusion Models Andreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas Müller Björn Ommer LMU Munich, MCML & IWR, Heidelberg University, Germany # Abstract Novel architectures have recently improved generative image synthesis leading to excellent visual quality in various tasks. Much of this...
/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference.pdf
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_0
[ { "category_id": 3, "latex": null, "poly": [ 1026.870849609375, 1318.16259765625, 1401.3565673828125, 1318.16259765625, 1401.3565673828125, 1572.4373779296875, 1026.870849609375, 1572.4373779296875 ], "score": 0.9999935030937195, "text": null ...
[]
[ "$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x\\mid\\mathcal{M}_{\\mathcal{D}}^{(k)})\n$$", "$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\{\\phi(y)\\mid y\\in\\xi_{k}(x,\\mathcal{D})\\}).\n$$", "$$\n\\operatorname*{min}_{\\theta}\\mathcal{L}=\...
[ { "caption": [ "Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] on ImageNet [13] and even reaches the class-conditional ADM (ADM w/ classifier), while reducing parameter count. $|\\mathcal D|$ : Number of instances in database at inference; $|\\theta|$ : Number of tra...
[]
0
[ 1224, 1584 ]
# Retrieval-Augmented Diffusion Models Andreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas Müller Björn Ommer LMU Munich, MCML & IWR, Heidelberg University, Germany # Abstract Novel architectures have recently improved generative image synthesis leading to excellent visual quality in various tasks. Much of this...
/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference.pdf
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_1
[ { "category_id": 3, "latex": null, "poly": [ 320.53668212890625, 200.24880981445312, 1380.3177490234375, 200.24880981445312, 1380.3177490234375, 684.8720703125, 320.53668212890625, 684.8720703125 ], "score": 0.9999944567680359, "text": null }...
[]
[ "$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x\\mid\\mathcal{M}_{\\mathcal{D}}^{(k)})\n$$", "$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\{\\phi(y)\\mid y\\in\\xi_{k}(x,\\mathcal{D})\\}).\n$$", "$$\n\\operatorname*{min}_{\\theta}\\mathcal{L}=\...
[ { "caption": [ "Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] on ImageNet [13] and even reaches the class-conditional ADM (ADM w/ classifier), while reducing parameter count. $|\\mathcal D|$ : Number of instances in database at inference; $|\\theta|$ : Number of tra...
[]
1
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_2
[{"category_id":1,"latex":null,"poly":[291.73199462890625,1097.4366455078125,1408.9388427734375,1097(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
2
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_3
[{"category_id":1,"latex":null,"poly":[297.4248962402344,837.9775390625,1404.4361572265625,837.97753(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
3
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_4
[{"category_id":8,"latex":null,"poly":[556.1173095703125,1567.1861572265625,1141.0675048828125,1567.(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
4
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_5
[{"category_id":3,"latex":null,"poly":[301.94305419921875,1255.6844482421875,1404.4149169921875,1255(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
5
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_6
[{"category_id":3,"latex":null,"poly":[905.5112915039062,1027.3095703125,1396.9708251953125,1027.309(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
6
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_7
[{"category_id":4,"latex":null,"poly":[1044.3299560546875,1321.4417724609375,1405.76904296875,1321.4(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
7
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_8
[{"category_id":1,"latex":null,"poly":[291.88189697265625,199.44927978515625,1050.05078125,199.44927(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
8
[ 1224, 1584 ]
"# Retrieval-Augmented Diffusion Models \n\nAndreas Blattmann∗ Robin Rombach∗ Kaan Oktay Jonas (...TRUNCATED)
"/Users/samarth/Documents/Samarth/CVPR/Nayana/pdfmathtranslate/miner/pdf/NeurIPS-2022-retrieval-augm(...TRUNCATED)
NeurIPS-2022-retrieval-augmented-diffusion-models-Paper-Conference_page_9
[{"category_id":1,"latex":null,"poly":[294.19329833984375,1134.177978515625,1407.2490234375,1134.177(...TRUNCATED)
[]
["$$\np_{\\theta,\\mathcal{D},\\xi_{k}}(x)=p_{\\theta}(x\\mid\\xi_{k}(x,\\mathcal{D}))=p_{\\theta}(x(...TRUNCATED)
[{"caption":["Figure 1: Our semi-parametric model outperforms the unconditional SOTA model ADM [15] (...TRUNCATED)
[]
9
[ 1224, 1584 ]
End of preview. Expand in Data Studio
README.md exists but content is empty.
Downloads last month
5