Muhammad Umair
umair894
		AI & ML interests
AI Researcher | Consultant | Engineer |PhD |6+ Years of Experience: 
Specializing in building AI-powered SaaS solutions and delivering innovative AI, generative AI, and multimodal use cases. I've successfully led and contributed to dozens of projects, creating impactful proofs of concept (PoCs) that drive business value.
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						ππ‘π New Research Alert - ICCV 2025 (Oral)! ππͺπ
π Title: LoftUp: Learning a Coordinate-based Feature Upsampler for Vision Foundation Models π
π Description: LoftUp is a coordinate-based transformer that upscales the low-resolution features of VFMs (e.g. DINOv2 and CLIP) using cross-attention and self-distilled pseudo-ground truth (pseudo-GT) from SAM.
π₯ Authors: Haiwen Huang, Anpei Chen, Volodymyr Havrylov, Andreas Geiger, and Dan Zhang
π
 Conference: ICCV, 19 β 23 Oct, 2025  | Honolulu, Hawai'i, USA πΊπΈ
π Paper: https://huggingface.co/papers/2504.14032
π Github Page: https://andrehuang.github.io/loftup-site
π Repository: https://github.com/andrehuang/loftup
π ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
π Added to the Foundation Models and Representation Learning Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/foundation-models-and-representation-learning.md
π More Papers: more cutting-edge research presented at other conferences in the https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
π Keywords: #LoftUp #VisionFoundationModels #FeatureUpsampling  #Cross-AttentionTransformer #CoordinateBasedLearning #SelfDistillation #PseudoGroundTruth #RepresentationLearning #AI #ICCV2025 #ResearchHighlight
						
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