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Found 11 papers, 6 papers with code
Learning to Route Among Specialized Experts for Zero-Shot Generalization
Unlike past methods that learn to route among specialized models, PHATGOOSE explores the possibility that zero-shot generalization will be improved if different experts can be adaptively chosen for each token and at each layer in the model.
I2V-Adapter: A General Image-to-Video Adapter for Diffusion Models
I2V-Adapter adeptly propagates the unnoised input image to subsequent noised frames through a cross-frame attention mechanism, maintaining the identity of the input image without any changes to the pretrained T2V model.
Protein-DNA binding sites prediction based on pre-trained protein language model and contrastive learning
We trained the CLAPE-DB model on the protein-DNA binding sites dataset and evaluated the model performance and generalization ability through various experiments.
AUNet: Learning Relations Between Action Units for Face Forgery Detection
Observing that face manipulation may alter the relation between different facial action units (AU), we propose the Action Units Relation Learning framework to improve the generality of forgery detection.
Cross-Architecture Knowledge Distillation
However, most existing knowledge distillation methods only consider homologous-architecture distillation, such as distilling knowledge from CNN to CNN.
Joint Learning of Visual-Audio Saliency Prediction and Sound Source Localization on Multi-face Videos
In this paper, we propose a multitask learning method for visual-audio saliency prediction and sound source localization on multi-face video by leveraging visual, audio and face information.
SDTP: Semantic-aware Decoupled Transformer Pyramid for Dense Image Prediction
CDI builds the global attention and interaction among different levels in decoupled space which also solves the problem of heavy computation.
Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model
Inspired by the findings of our investigation, we propose a novel multi-modal video saliency model consisting of three branches: visual, audio and face.
DSIC: Dynamic Sample-Individualized Connector for Multi-Scale Object Detection
Furthermore, these two components are both plug-and-play and can be embedded in any backbone.
Knowledge Distillation via Instance Relationship Graph
The key challenge of knowledge distillation is to extract general, moderate and sufficient knowledge from a teacher network to guide a student network.
Predicting Salient Face in Multiple-Face Videos
On the other hand, we find that the attention of different subjects consistently focuses on a single face in each frame of videos involving multiple faces.
