Loading the SOTA2 catalog…
SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Julien Posso, Hugo Kieffer, Nicolas Menga |
| 2025 |
| arxiv 2503.08700 |
| Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation | Peng-Tao Jiang, Yuqi Yang | 2023 | arxiv 2305.01275 |
|---|
| Semantic Segmentation on VSPW Dataset through Contrastive Loss and Multi-dataset Training Approach | Min Yan, Qianxiong Ning, Qian Wang | 2023 | arxiv 2306.03508 |
|---|
| A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation | Lokesh Veeramacheneni, Matias Valdenegro-Toro | 2022 | arxiv 2211.06241 |
|---|
| Union-set Multi-source Model Adaptation for Semantic Segmentation | Zongyao Li, Ren Togo, Takahiro Ogawa | 2022 | arxiv 2212.02785 |
|---|
| AFRDA: Attentive Feature Refinement for Domain Adaptive Semantic Segmentation | Md. Al-Masrur Khan, Durgakant Pushp, Lantao Liu | 2025 | arxiv 2507.17957 |
|---|
| Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation | Zhenliang Ni, Xinghao Chen, Yingjie Zhai | 2024 | arxiv 2405.06228 |
|---|
| CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation | Yu Qiao, Jincheng Zhu, Chengjiang Long | 2021 | arxiv 2112.05975 |
|---|
| Learning Semantic Segmentation from Multiple Datasets with Label Shifts | Dongwan Kim, Yi-Hsuan Tsai, Yumin Suh | 2022 | arxiv 2202.14030 |
|---|
| Reliability in Semantic Segmentation: Can We Use Synthetic Data? | Thibaut Loiseau, Tuan-Hung Vu, Mickael Chen | 2023 | arxiv 2312.09231 |
|---|
| DUDA: Distilled Unsupervised Domain Adaptation for Lightweight Semantic Segmentation | Beomseok Kang, Niluthpol Chowdhury Mithun, Abhinav Rajvanshi | 2025 | arxiv 2504.09814 |
|---|
| Spectral-Aware Global Fusion for RGB-Thermal Semantic Segmentation | Ce Zhang, Zifu Wan, Simon Stepputtis | 2025 | arxiv 2505.15491 |
|---|