Copertina

The Surprising Effectiveness of Canonical Knowledge Distillation for Semantic Segmentation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ali, Muhammad, Laube, Kevin Alexander, Ganesh, Madan Ravi, Schott, Lukas, Popp, Niclas, Brox, Thomas
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation
di: Popp, Niclas, et al.
Pubblicazione: (2025)

Zero-Shot Distillation for Image Encoders: How to Make Effective Use of Synthetic Data
di: Popp, Niclas, et al.
Pubblicazione: (2024)

Single-Pass Object-Focused Data Selection
di: Popp, Niclas, et al.
Pubblicazione: (2024)

SlotMatch: Distilling Object-Centric Representations for Unsupervised Video Segmentation
di: Grigore, Diana-Nicoleta, et al.
Pubblicazione: (2025)

Attention Is All You Need For Mixture-of-Depths Routing
di: Gadhikar, Advait, et al.
Pubblicazione: (2024)

Label-free Neural Semantic Image Synthesis
di: Wang, Jiayi, et al.
Pubblicazione: (2024)

Early Exit and Multi Stage Knowledge Distillation in VLMs for Video Summarization
di: Khan, Anas Anwarul Haq, et al.
Pubblicazione: (2025)

StorySync: Training-Free Subject Consistency in Text-to-Image Generation via Region Harmonization
di: Gaur, Gopalji, et al.
Pubblicazione: (2025)

KDMOS:Knowledge Distillation for Motion Segmentation
di: Cao, Chunyu, et al.
Pubblicazione: (2025)

Hybrid(Transformer+CNN)-based Polyp Segmentation
di: Baduwal, Madan
Pubblicazione: (2025)

DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation
di: Landgraf, Steven, et al.
Pubblicazione: (2023)

MicroAUNet: Boundary-Enhanced Multi-scale Fusion with Knowledge Distillation for Colonoscopy Polyp Image Segmentation
di: Wang, Ziyi, et al.
Pubblicazione: (2025)

D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation
di: Zheng, Wenjie, et al.
Pubblicazione: (2026)

Structural and Statistical Texture Knowledge Distillation for Semantic Segmentation
di: Ji, Deyi, et al.
Pubblicazione: (2023)

On the Surprising Effectiveness of Attention Transfer for Vision Transformers
di: Li, Alexander C., et al.
Pubblicazione: (2024)

Label-Efficient LiDAR Semantic Segmentation with 2D-3D Vision Transformer Adapters
di: Hindel, Julia, et al.
Pubblicazione: (2025)

Towards Effective Data-Free Knowledge Distillation via Diverse Diffusion Augmentation
di: Li, Muquan, et al.
Pubblicazione: (2024)

Rethinking RGB-D Fusion for Semantic Segmentation in Surgical Datasets
di: Jamal, Muhammad Abdullah, et al.
Pubblicazione: (2024)

Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation
di: Li, Ping, et al.
Pubblicazione: (2023)

Deep Learning-Based 3D Instance and Semantic Segmentation: A Review
di: Yasir, Siddiqui Muhammad, et al.
Pubblicazione: (2024)

FSKD: Monocular Forest Structure Inference via LiDAR-to-RGBI Knowledge Distillation
di: Khan, Taimur, et al.
Pubblicazione: (2026)

Knowledge Distillation for Semantic Segmentation: A Label Space Unification Approach
di: Backhaus, Anton, et al.
Pubblicazione: (2025)

Generalizable Knowledge Distillation from Vision Foundation Models for Semantic Segmentation
di: Lv, Chonghua, et al.
Pubblicazione: (2026)

Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
di: Puglisi, Lemuel, et al.
Pubblicazione: (2024)

LIFT and PLACE: A Simple, Stable, and Effective Knowledge Distillation Framework for Lightweight Diffusion Models
di: Han, Hyunsoo, et al.
Pubblicazione: (2026)

BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations
di: Monninger, Thomas, et al.
Pubblicazione: (2026)

Investigating the Semantic Robustness of CLIP-based Zero-Shot Anomaly Segmentation
di: Stangl, Kevin, et al.
Pubblicazione: (2024)

SOccDPT: Semi-Supervised 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints
di: Ganesh, Aditya Nalgunda
Pubblicazione: (2023)

Distilling Knowledge from Heterogeneous Architectures for Semantic Segmentation
di: Huang, Yanglin, et al.
Pubblicazione: (2025)

MorphDistill: Distilling Unified Morphological Knowledge from Pathology Foundation Models for Colorectal Cancer Survival Prediction
di: Khan, Hikmat, et al.
Pubblicazione: (2026)

Semantic Segmentation by Semantic Proportions
di: Aysel, Halil Ibrahim, et al.
Pubblicazione: (2023)

Diffusion for Out-of-Distribution Detection on Road Scenes and Beyond
di: Galesso, Silvio, et al.
Pubblicazione: (2024)

TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models
di: Weijler, Lisa, et al.
Pubblicazione: (2024)

Adaptive Explicit Knowledge Transfer for Knowledge Distillation
di: Park, Hyungkeun, et al.
Pubblicazione: (2024)

Efficient Knowledge Distillation of SAM for Medical Image Segmentation
di: Patil, Kunal Dasharath, et al.
Pubblicazione: (2025)

Diffusion-Guided Knowledge Distillation for Weakly-Supervised Low-Light Semantic Segmentation
di: Wang, Chunyan, et al.
Pubblicazione: (2025)

I2CKD : Intra- and Inter-Class Knowledge Distillation for Semantic Segmentation
di: Karine, Ayoub, et al.
Pubblicazione: (2024)

Knowledge-Guided Brain Tumor Segmentation via Synchronized Visual-Semantic-Topological Prior Fusion
di: Zhang, Mingda, et al.
Pubblicazione: (2025)

Understanding the Role of the Projector in Knowledge Distillation
di: Miles, Roy, et al.
Pubblicazione: (2023)

Graph Attention Convolutional U-NET: A Semantic Segmentation Model for Identifying Flooded Areas
di: Danish, Muhammad Umair, et al.
Pubblicazione: (2025)