This paper presents a novel approach to open-set semantic segmentation in unstructured environments where there are no meaningful prior mask proposals. Our method leverages pretrained encoders from foundation models and uses image-caption datasets for training, reducing the need for ...
A Prototypical Metric Learning Approach for Open-Set Semantic Segmentation on Remote Sensing Images Semantic segmentation has received wide attention as a feasible solution to effectively interpret the information in remote sensing images. Solutions are t......
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application Continual learning, also known as incremental learning or life-long learning, stands at the forefront of deep learning and AI systems. It breaks through th... B Yuan,D Zhao - 《IEEE Transactions on Pattern An...
Missing setup instructions for the semantic_inference_ros environment. A tf_lookup error when running Clio, leading to dropped camera features. Pre-generating Open-set Semantics It's useful to pre-generate the open-set segmentation and CLIP embeddings before running Clio. For example: ...
《Open-World Semantic Segmentation Including Class Similarity》(CVPR 2024) GitHub: github.com/PRBonn/ContMAV《Semantic Gaussians: Open-Vocabulary Scene Understanding with 3D Gaussian Splatting》(CVPR 2024) GitHub: github.com/sharinka0715/semantic-gaussians...
Generation Semantic map HF Hub Generation Normal map HF Hub Note that the provided checkpoint for semantic map is only trained on ADE20K dataset; the checkpoint for normal map is only trained on DIODE dataset. Inference: Generate images with GLIGEN We provide one script to generate images using...
Encoder-decoder with atrous separable convolution for semantic image segmentation X. Chen et al. A boundary based out-of-distribution classifier for generalized zero-shot learning Y. Chen et al. Semi-supervised learning under class distribution mismatchView more references ...
Deep Metric Learning for Open World Semantic Segmentation. Jun Cen, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu. (ICCV 2021) NGC: A Unified Framework for Learning With Open-World Noisy Data. Zhi-Fan Wu, Tong Wei, Jianwen Jiang, Chaojie Mao, Mingqian Tang, Yu-Feng Li. (ICCV 2021...
2023/07/18: We releaseSemantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity.Codeandcheckpointare available! 2023/06/17: We provide an example to evaluate Grounding DINO on COCO zero-shot performance. ...
OpenGAN-0fea.999.998.997.999.964.996.996.946.952.992.994.934.994.995.992.997.984 OpenGANfea.999.999.990.973.974.999.996.971.976.998.999.967.973.968.970.999.984 Table 5: Comparison in open-setsemantic segmentationon Cityscapes (AUROC↑). All methods are implemented on top of the segmentation network HRN...