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LMSeg: Unleashing the Power of Large-Scale Models for Open-Vocabulary Semantic Segmentation
Arxiv
0+阅读 · 2月18日
Language-Guided Invariance Probing of Vision-Language Models
Arxiv
0+阅读 · 2月18日
A Contrastive Learning Framework Empowered by Attention-based Feature Adaptation for Street-View Image Classification
Arxiv
0+阅读 · 2月18日
MedProbCLIP: Probabilistic Adaptation of Vision-Language Foundation Model for Reliable Radiograph-Report Retrieval
Arxiv
0+阅读 · 2月17日
Visual Word Sense Disambiguation with CLIP through Dual-Channel Text Prompting and Image Augmentations
Arxiv
0+阅读 · 2月6日
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
Arxiv
0+阅读 · 2月7日
Inspiration Seeds: Learning Non-Literal Visual Combinations for Generative Exploration
Arxiv
0+阅读 · 2月12日
Inspiration Seeds: Learning Non-Literal Visual Combinations for Generative Exploration
Arxiv
0+阅读 · 2月9日
Inject Where It Matters: Training-Free Spatially-Adaptive Identity Preservation for Text-to-Image Personalization
Arxiv
0+阅读 · 2月15日
UniLiP: Adapting CLIP for Unified Multimodal Understanding, Generation and Editing
Arxiv
0+阅读 · 2月9日
Closing the Confusion Loop: CLIP-Guided Alignment for Source-Free Domain Adaptation
Arxiv
0+阅读 · 2月9日
Image-to-Image Translation with Diffusion Transformers and CLIP-Based Image Conditioning
Arxiv
0+阅读 · 2月5日
CLIP-Map: Structured Matrix Mapping for Parameter-Efficient CLIP Compression
CLIP-Map: Structured Matrix Mapping for Parameter-Efficient CLIP Compression
Arxiv
1+阅读 · 2月5日
DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection
Arxiv
0+阅读 · 2月4日
Explicit Uncertainty Modeling for Active CLIP Adaptation with Dual Prompt Tuning
Arxiv
0+阅读 · 2月4日
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