Learning conditional attributes for compositional zero-shot learning
Abstract Compositional Zero-Shot Learning (CZSL) aims to train models to recognize novel
compositional concepts based on learned concepts such as attribute-object combinations …
compositional concepts based on learned concepts such as attribute-object combinations …
Learning attention as disentangler for compositional zero-shot learning
Compositional zero-shot learning (CZSL) aims at learning visual concepts (ie, attributes and
objects) from seen compositions and combining concept knowledge into unseen …
objects) from seen compositions and combining concept knowledge into unseen …
Hierarchical visual primitive experts for compositional zero-shot learning
Compositional zero-shot learning (CZSL) aims to recognize unseen compositions with prior
knowledge of known primitives (attribute and object). Previous works for CZSL often suffer …
knowledge of known primitives (attribute and object). Previous works for CZSL often suffer …
Drpt: Disentangled and recurrent prompt tuning for compositional zero-shot learning
Compositional Zero-shot Learning (CZSL) aims to recognize novel concepts composed of
known knowledge without training samples. Standard CZSL either identifies visual primitives …
known knowledge without training samples. Standard CZSL either identifies visual primitives …
Joint Image and Feature Levels Disentanglement for Generalizable Vehicle Re-identification
Domain generalization (DG), which doesn't require any data from target domains during
training, is more challenging but practical than unsupervised domain adaptation (UDA) …
training, is more challenging but practical than unsupervised domain adaptation (UDA) …
Troika: Multi-path cross-modal traction for compositional zero-shot learning
Recent compositional zero-shot learning (CZSL) methods adapt pre-trained vision-language
models (VLMs) by constructing trainable prompts only for composed state-object pairs …
models (VLMs) by constructing trainable prompts only for composed state-object pairs …
Retrieval-Augmented Primitive Representations for Compositional Zero-Shot Learning
Compositional zero-shot learning (CZSL) aims to recognize unseen attribute-object
compositions by learning from seen compositions. Composing the learned knowledge of …
compositions by learning from seen compositions. Composing the learned knowledge of …
Prompting language-informed distribution for compositional zero-shot learning
Compositional zero-shot learning (CZSL) task aims to recognize unseen compositional
visual concepts, eg, sliced tomatoes, where the model is learned only from the seen …
visual concepts, eg, sliced tomatoes, where the model is learned only from the seen …
Simple primitives with feasibility-and contextuality-dependence for open-world compositional zero-shot learning
The task of Open-World Compositional Zero-Shot Learning (OW-CZSL) is to recognize novel
state-object compositions in images from all possible compositions, where the novel …
state-object compositions in images from all possible compositions, where the novel …
Compositional zero-shot learning via progressive language-based observations
Compositional zero-shot learning aims to recognize unseen state-object compositions by
leveraging known primitives (state and object) during training. However, effectively modeling …
leveraging known primitives (state and object) during training. However, effectively modeling …