SigLino: Vision Foundation Models (SigLIP2 + DINOv3)
Collection
Vision encoders distilled from DINOv3 and SigLIP2 (MoE & Dense). CVPR 2026. ā¢ 6 items ā¢ Updated ā¢ 16
Dmitry Ryumin
DmitryRyumin
AI & ML interests
Machine Learning and Applications, Multi-Modal Understanding
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SigLino: Vision Foundation Models (SigLIP2 + DINOv3) liked a dataset 12 days ago
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Article
Fine-Tuning MetaCLIP-2 for Image Classification on Downstream Tasks
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reactedto prithivMLmods's post with ššā¤ļøš¤ 5 months ago
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Made a small write up and experimental finetuning guide for MetaCLIP2 for Image Classification on Downstream Tasks. The blog titled
ā® Blog Article: https://huggingface.co/blog/prithivMLmods/metaclip2-downstream-finetune
ā® Demo Space[Zero-Shot Classification]: prithivMLmods/metaclip-2-demo
Some other models
ā°āŗ MetaCLIP-2-Cifar10: prithivMLmods/MetaCLIP-2-Cifar10
ā°āŗ MetaCLIP-2-Age-Range-Estimator: prithivMLmods/MetaCLIP-2-Age-Range-Estimator
ā°āŗ MetaCLIP-2-Gender-Identifier: prithivMLmods/MetaCLIP-2-Gender-Identifier
ā°āŗ MetaCLIP-2-Open-Scene: prithivMLmods/MetaCLIP-2-Open-Scene
ā® Collection: https://huggingface.co/collections/prithivMLmods/metaclip2-image-classification-experiments
To know more about it, visit the app page or the respective model page!
Fine Tuning MetaCLIP 2 for Image Classification on Downstream Tasks demonstrates the step by step finetuning using CIFAR10 and is also flexible for adapting to other datasets. For more details, check out the linked blog below. š¤āļøā® Blog Article: https://huggingface.co/blog/prithivMLmods/metaclip2-downstream-finetune
ā® Demo Space[Zero-Shot Classification]: prithivMLmods/metaclip-2-demo
Some other models
ā°āŗ MetaCLIP-2-Cifar10: prithivMLmods/MetaCLIP-2-Cifar10
ā°āŗ MetaCLIP-2-Age-Range-Estimator: prithivMLmods/MetaCLIP-2-Age-Range-Estimator
ā°āŗ MetaCLIP-2-Gender-Identifier: prithivMLmods/MetaCLIP-2-Gender-Identifier
ā°āŗ MetaCLIP-2-Open-Scene: prithivMLmods/MetaCLIP-2-Open-Scene
ā® Collection: https://huggingface.co/collections/prithivMLmods/metaclip2-image-classification-experiments
To know more about it, visit the app page or the respective model page!
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Space 5 months ago
reactedto their post with š„ 5 months ago
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ššļøš New Research Alert - ICCV 2025 (Poster)! ššļøš
š Title: Is Less More? Exploring Token Condensation as Training-Free Test-Time Adaptation š
š Description: Token Condensation as Adaptation (TCA) improves the performance and efficiency of Vision Language Models in zero-shot inference by introducing domain anchor tokens.
š„ Authors: Zixin Wang, Dong Gong, Sen Wang, Zi Huang, Yadan Luo
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation (2410.14729)
š Repository: https://github.com/Jo-wang/TCA
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the Session 1: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/session-1.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #TestTimeAdaptation #TokenCondensation #VisionLanguageModels #TrainingFreeAdaptation #ZeroShotLearning #EfficientAI #AI #ICCV2025 #ResearchHighlight
š Title: Is Less More? Exploring Token Condensation as Training-Free Test-Time Adaptation š
š Description: Token Condensation as Adaptation (TCA) improves the performance and efficiency of Vision Language Models in zero-shot inference by introducing domain anchor tokens.
š„ Authors: Zixin Wang, Dong Gong, Sen Wang, Zi Huang, Yadan Luo
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation (2410.14729)
š Repository: https://github.com/Jo-wang/TCA
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the Session 1: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/session-1.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #TestTimeAdaptation #TokenCondensation #VisionLanguageModels #TrainingFreeAdaptation #ZeroShotLearning #EfficientAI #AI #ICCV2025 #ResearchHighlight
posted an update 5 months ago
Post
1332
ššļøš New Research Alert - ICCV 2025 (Poster)! ššļøš
š Title: Is Less More? Exploring Token Condensation as Training-Free Test-Time Adaptation š
š Description: Token Condensation as Adaptation (TCA) improves the performance and efficiency of Vision Language Models in zero-shot inference by introducing domain anchor tokens.
š„ Authors: Zixin Wang, Dong Gong, Sen Wang, Zi Huang, Yadan Luo
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation (2410.14729)
š Repository: https://github.com/Jo-wang/TCA
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the Session 1: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/session-1.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #TestTimeAdaptation #TokenCondensation #VisionLanguageModels #TrainingFreeAdaptation #ZeroShotLearning #EfficientAI #AI #ICCV2025 #ResearchHighlight
š Title: Is Less More? Exploring Token Condensation as Training-Free Test-Time Adaptation š
š Description: Token Condensation as Adaptation (TCA) improves the performance and efficiency of Vision Language Models in zero-shot inference by introducing domain anchor tokens.
š„ Authors: Zixin Wang, Dong Gong, Sen Wang, Zi Huang, Yadan Luo
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation (2410.14729)
š Repository: https://github.com/Jo-wang/TCA
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the Session 1: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/session-1.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #TestTimeAdaptation #TokenCondensation #VisionLanguageModels #TrainingFreeAdaptation #ZeroShotLearning #EfficientAI #AI #ICCV2025 #ResearchHighlight
upvoted a paper 5 months ago
liked a
dataset 5 months ago
liked a
model 5 months ago
reactedto their post with š 5 months ago
Post
2464
ššļøš New Research Alert - ICCV 2025 (Oral)! ššļøš
š Title: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching š
š Description: The proposed method enhances stereo matching by efficiently combining unbiased monocular priors from vision foundation models. This method addresses misalignment and local optima issues using a binary local ordering map and pixel-wise linear regression.
š„ Authors: Chengtang Yao, Lidong Yu, Zhidan Liu, Jiaxi Zeng, Yuwei Wu, and Yunde Jia
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching (2505.14414)
š Repository: https://github.com/YaoChengTang/Diving-into-the-Fusion-of-Monocular-Priors-for-Generalized-Stereo-Matching
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the 3D Pose Understanding Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/3d-pose-understanding.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #StereoMatching #MonocularDepth #VisionFoundationModels #3DReconstruction #Generalization #AI #ICCV2025 #ResearchHighlight
š Title: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching š
š Description: The proposed method enhances stereo matching by efficiently combining unbiased monocular priors from vision foundation models. This method addresses misalignment and local optima issues using a binary local ordering map and pixel-wise linear regression.
š„ Authors: Chengtang Yao, Lidong Yu, Zhidan Liu, Jiaxi Zeng, Yuwei Wu, and Yunde Jia
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching (2505.14414)
š Repository: https://github.com/YaoChengTang/Diving-into-the-Fusion-of-Monocular-Priors-for-Generalized-Stereo-Matching
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the 3D Pose Understanding Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/3d-pose-understanding.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #StereoMatching #MonocularDepth #VisionFoundationModels #3DReconstruction #Generalization #AI #ICCV2025 #ResearchHighlight
posted an update 5 months ago
Post
2464
ššļøš New Research Alert - ICCV 2025 (Oral)! ššļøš
š Title: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching š
š Description: The proposed method enhances stereo matching by efficiently combining unbiased monocular priors from vision foundation models. This method addresses misalignment and local optima issues using a binary local ordering map and pixel-wise linear regression.
š„ Authors: Chengtang Yao, Lidong Yu, Zhidan Liu, Jiaxi Zeng, Yuwei Wu, and Yunde Jia
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching (2505.14414)
š Repository: https://github.com/YaoChengTang/Diving-into-the-Fusion-of-Monocular-Priors-for-Generalized-Stereo-Matching
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the 3D Pose Understanding Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/3d-pose-understanding.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #StereoMatching #MonocularDepth #VisionFoundationModels #3DReconstruction #Generalization #AI #ICCV2025 #ResearchHighlight
š Title: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching š
š Description: The proposed method enhances stereo matching by efficiently combining unbiased monocular priors from vision foundation models. This method addresses misalignment and local optima issues using a binary local ordering map and pixel-wise linear regression.
š„ Authors: Chengtang Yao, Lidong Yu, Zhidan Liu, Jiaxi Zeng, Yuwei Wu, and Yunde Jia
š Conference: ICCV, 19 ā 23 Oct, 2025 | Honolulu, Hawai'i, USA šŗšø
š Paper: Diving into the Fusion of Monocular Priors for Generalized Stereo Matching (2505.14414)
š Repository: https://github.com/YaoChengTang/Diving-into-the-Fusion-of-Monocular-Priors-for-Generalized-Stereo-Matching
š ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
š Added to the 3D Pose Understanding Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/3d-pose-understanding.md
š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
š Keywords: #StereoMatching #MonocularDepth #VisionFoundationModels #3DReconstruction #Generalization #AI #ICCV2025 #ResearchHighlight