Trackio logbook, compact outputs, and artifact Bucket for reproducing Olaf-World (arXiv 2602.10104, OpenReview 5TiuerrwR8).
Niels Rogge
nielsr
AI & ML interests
Mainly interested in diving into complex Github repos and making AI easier and more accessible to everyone
Recent Activity
updated a dataset 5 minutes ago
nielsr/r3al-vit-quantization-codex-trace published a dataset 5 minutes ago
nielsr/r3al-vit-quantization-codex-trace new activity about 4 hours ago
Lewandofski/OpenVE-3M:Update task category and add GitHub linkOrganizations
SigLIP release
SigLIP improves upon CLIP with a sigmoid loss. Both English-only and multilingual checkpoints are released.
-
Sigmoid Loss for Language Image Pre-Training
Paper • 2303.15343 • Published • 12 -
google/siglip-base-patch16-224
Zero-Shot Image Classification • 0.2B • Updated • 1.38M • 88 -
google/siglip-base-patch16-256
Zero-Shot Image Classification • 0.2B • Updated • 23.9k • 7 -
google/siglip-base-patch16-384
Zero-Shot Image Classification • 0.2B • Updated • 26.9k • 11
DPT 3.1 release
DPT 3.1 (MiDaS) models, leveraging state-of-the-art vision backbones such as BEiT and Swinv2
-
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer
Paper • 1907.01341 • Published • 1 -
Intel/dpt-beit-large-512
Depth Estimation • 0.3B • Updated • 484 • 9 -
Intel/dpt-beit-large-384
Depth Estimation • 0.3B • Updated • 211 -
Intel/dpt-beit-base-384
Depth Estimation • 0.1B • Updated • 3.76k • 1
Image-to-text models
Collection of image captioning models
-
Salesforce/blip-image-captioning-large
Image-to-Text • 0.5B • Updated • 470k • 1.49k -
microsoft/git-large-coco
Image-to-Text • 0.4B • Updated • 3.73k • 106 -
Salesforce/instructblip-vicuna-7b
Image-Text-to-Text • 8B • Updated • 6.54k • 102 -
Salesforce/blip2-flan-t5-xxl
Image-Text-to-Text • 12B • Updated • 707 • 94
DPT 3.0 release
DPT 3.0 (MiDaS) models, leveraging ViT and ViT-hybrid backbones
Depth Anything release
Depth Anything models, which are monocular depth estimation models trained on 62 million images
-
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
LiheYoung/depth-anything-large-hf
Depth Estimation • 0.3B • Updated • 348k • 65 -
LiheYoung/depth-anything-base-hf
Depth Estimation • 97.5M • Updated • 46.9k • 12 -
LiheYoung/depth-anything-small-hf
Depth Estimation • 24.8M • Updated • 52k • 36
Olaf-World ICML 2026 Reproduction
Trackio logbook, compact outputs, and artifact Bucket for reproducing Olaf-World (arXiv 2602.10104, OpenReview 5TiuerrwR8).
Image-to-text models
Collection of image captioning models
-
Salesforce/blip-image-captioning-large
Image-to-Text • 0.5B • Updated • 470k • 1.49k -
microsoft/git-large-coco
Image-to-Text • 0.4B • Updated • 3.73k • 106 -
Salesforce/instructblip-vicuna-7b
Image-Text-to-Text • 8B • Updated • 6.54k • 102 -
Salesforce/blip2-flan-t5-xxl
Image-Text-to-Text • 12B • Updated • 707 • 94
SigLIP release
SigLIP improves upon CLIP with a sigmoid loss. Both English-only and multilingual checkpoints are released.
-
Sigmoid Loss for Language Image Pre-Training
Paper • 2303.15343 • Published • 12 -
google/siglip-base-patch16-224
Zero-Shot Image Classification • 0.2B • Updated • 1.38M • 88 -
google/siglip-base-patch16-256
Zero-Shot Image Classification • 0.2B • Updated • 23.9k • 7 -
google/siglip-base-patch16-384
Zero-Shot Image Classification • 0.2B • Updated • 26.9k • 11
DPT 3.0 release
DPT 3.0 (MiDaS) models, leveraging ViT and ViT-hybrid backbones
DPT 3.1 release
DPT 3.1 (MiDaS) models, leveraging state-of-the-art vision backbones such as BEiT and Swinv2
-
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer
Paper • 1907.01341 • Published • 1 -
Intel/dpt-beit-large-512
Depth Estimation • 0.3B • Updated • 484 • 9 -
Intel/dpt-beit-large-384
Depth Estimation • 0.3B • Updated • 211 -
Intel/dpt-beit-base-384
Depth Estimation • 0.1B • Updated • 3.76k • 1
Depth Anything release
Depth Anything models, which are monocular depth estimation models trained on 62 million images
-
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
LiheYoung/depth-anything-large-hf
Depth Estimation • 0.3B • Updated • 348k • 65 -
LiheYoung/depth-anything-base-hf
Depth Estimation • 97.5M • Updated • 46.9k • 12 -
LiheYoung/depth-anything-small-hf
Depth Estimation • 24.8M • Updated • 52k • 36