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Found 7 papers, 5 papers with code
DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer
Existing SDS methods often struggle with this generation task due to a limited understanding of part-level semantics in text-to-image diffusion models.
kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
We demonstrate that kNN-CLIP can adapt to continually growing vocabularies without the need for retraining or large memory costs.
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
The former arises from non-uniform point sampling, allowing models to distinguish the density disparities between foreground and background for easier segmentation.
Few-shot 3D Point Cloud Semantic Segmentation
Segmentation
+1
Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation
Modern approaches have proved the huge potential of addressing semantic segmentation as a mask classification task which is widely used in instance-level segmentation.
Indiscernible Object Counting in Underwater Scenes
We further advance the frontier of this field by systematically studying a new challenge named indiscernible object counting (IOC), the goal of which is to count objects that are blended with respect to their surroundings.
EM-RBR: a reinforced framework for knowledge graph completion from reasoning perspective
To solve this problem, in this paper, we propose a general framework, named EM-RBR(embedding and rule-based reasoning), capable of combining the advantages of reasoning based on rules and the state-of-the-art models of embedding.
