MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Zhenyu, Chen, Guangyao, Zou, Yixiong, Huang, Zhimeng, Li, Yuhua, Li, Ruixuan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026)
by: Zhang, Zhenyu, et al.
Published: (2026)
Decoupling Template Bias in CLIP: Harnessing Empty Prompts for Enhanced Few-Shot Learning
by: Zhang, Zhenyu, et al.
Published: (2025)
by: Zhang, Zhenyu, et al.
Published: (2025)
Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition
by: Zhang, Zhenyu, et al.
Published: (2024)
by: Zhang, Zhenyu, et al.
Published: (2024)
Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning
by: Jiang, Yongwei, et al.
Published: (2025)
by: Jiang, Yongwei, et al.
Published: (2025)
Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
by: Yi, Shuai, et al.
Published: (2025)
by: Yi, Shuai, et al.
Published: (2025)
Random Registers for Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2025)
by: Yi, Shuai, et al.
Published: (2025)
Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
by: Tong, Jintao, et al.
Published: (2025)
by: Tong, Jintao, et al.
Published: (2025)
Reviving In-domain Fine-tuning Methods for Source-Free Cross-domain Few-shot Learning
by: Zhao, Yaze, et al.
Published: (2026)
by: Zhao, Yaze, et al.
Published: (2026)
Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning
by: Ma, Ran, et al.
Published: (2024)
by: Ma, Ran, et al.
Published: (2024)
Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2026)
by: Yi, Shuai, et al.
Published: (2026)
Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2026)
by: Yi, Shuai, et al.
Published: (2026)
Remedying Target-Domain Astigmatism for Cross-Domain Few-Shot Object Detection
by: Jiang, Yongwei, et al.
Published: (2026)
by: Jiang, Yongwei, et al.
Published: (2026)
Interpretable Cross-Domain Few-Shot Learning with Rectified Target-Domain Local Alignment
by: Zhao, Yaze, et al.
Published: (2026)
by: Zhao, Yaze, et al.
Published: (2026)
Compositional Few-Shot Class-Incremental Learning
by: Zou, Yixiong, et al.
Published: (2024)
by: Zou, Yixiong, et al.
Published: (2024)
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2025)
by: Tong, Jintao, et al.
Published: (2025)
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2024)
by: Tong, Jintao, et al.
Published: (2024)
The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
by: Liu, Yuhan, et al.
Published: (2025)
by: Liu, Yuhan, et al.
Published: (2025)
Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning
by: Zou, Yixiong, et al.
Published: (2024)
by: Zou, Yixiong, et al.
Published: (2024)
Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning
by: Zhou, Haichen, et al.
Published: (2024)
by: Zhou, Haichen, et al.
Published: (2024)
FlowCut: Rethinking Redundancy via Information Flow for Efficient Vision-Language Models
by: Tong, Jintao, et al.
Published: (2025)
by: Tong, Jintao, et al.
Published: (2025)
Start Small, Think Big: Curriculum-based Relative Policy Optimization for Visual Grounding
by: Yan, Qingyang, et al.
Published: (2025)
by: Yan, Qingyang, et al.
Published: (2025)
Few-Shot Object Detection via Spatial-Channel State Space Model
by: Xin, Zhimeng, et al.
Published: (2025)
by: Xin, Zhimeng, et al.
Published: (2025)
Adaptive Prompt Learning with SAM for Few-shot Scanning Probe Microscope Image Segmentation
by: Shen, Yao, et al.
Published: (2024)
by: Shen, Yao, et al.
Published: (2024)
Rethinking Few-shot Class-incremental Learning: Learning from Yourself
by: Tang, Yu-Ming, et al.
Published: (2024)
by: Tang, Yu-Ming, et al.
Published: (2024)
Reclaiming Lost Text Layers for Source-Free Cross-Domain Few-Shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026)
by: Zhang, Zhenyu, et al.
Published: (2026)
Beyond Mask: Rethinking Guidance Types in Few-shot Segmentation
by: Chang, Shijie, et al.
Published: (2024)
by: Chang, Shijie, et al.
Published: (2024)
The Devil is in the Few Shots: Iterative Visual Knowledge Completion for Few-shot Learning
by: Li, Yaohui, et al.
Published: (2024)
by: Li, Yaohui, et al.
Published: (2024)
Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification
by: Rong, Jintao, et al.
Published: (2023)
by: Rong, Jintao, et al.
Published: (2023)
Connecting the Dots: Training-Free Visual Grounding via Agentic Reasoning
by: Luo, Liqin, et al.
Published: (2025)
by: Luo, Liqin, et al.
Published: (2025)
Few-shot Unknown Class Discovery of Hyperspectral Images with Prototype Learning and Clustering
by: Liu, Chun, et al.
Published: (2025)
by: Liu, Chun, et al.
Published: (2025)
Few-shot Object Localization
by: Ren, Yunhan, et al.
Published: (2024)
by: Ren, Yunhan, et al.
Published: (2024)
Few-shot Novel Category Discovery
by: Li, Chunming, et al.
Published: (2025)
by: Li, Chunming, et al.
Published: (2025)
Few-shot Calligraphy Style Learning
by: Chen, Fangda, et al.
Published: (2024)
by: Chen, Fangda, et al.
Published: (2024)
Enhancing Environmental Robustness in Few-shot Learning via Conditional Representation Learning
by: Guo, Qianyu, et al.
Published: (2025)
by: Guo, Qianyu, et al.
Published: (2025)
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
by: An, Zhaochong, et al.
Published: (2024)
by: An, Zhaochong, et al.
Published: (2024)
Unsupervised Object-Centric Learning from Multiple Unspecified Viewpoints
by: Yuan, Jinyang, et al.
Published: (2024)
by: Yuan, Jinyang, et al.
Published: (2024)
Rethinking Alignment and Uniformity in Unsupervised Semantic Segmentation
by: Zhang, Daoan, et al.
Published: (2022)
by: Zhang, Daoan, et al.
Published: (2022)
Preserve and Sculpt: Manifold-Aligned Fine-tuning of Vision-Language Models for Few-Shot Learning
by: Chen, Dexia, et al.
Published: (2025)
by: Chen, Dexia, et al.
Published: (2025)
SENet: A Spectral Filtering Approach to Represent Exemplars for Few-shot Learning
by: Zhang, Tao, et al.
Published: (2023)
by: Zhang, Tao, et al.
Published: (2023)
SwimBird: Eliciting Switchable Reasoning Mode in Hybrid Autoregressive MLLMs
by: Tong, Jintao, et al.
Published: (2026)
by: Tong, Jintao, et al.
Published: (2026)
Similar Items
-
Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026) -
Decoupling Template Bias in CLIP: Harnessing Empty Prompts for Enhanced Few-Shot Learning
by: Zhang, Zhenyu, et al.
Published: (2025) -
Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition
by: Zhang, Zhenyu, et al.
Published: (2024) -
Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning
by: Jiang, Yongwei, et al.
Published: (2025) -
Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
by: Yi, Shuai, et al.
Published: (2025)