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Found 6 papers, 4 papers with code
Block Pruning for Enhanced Efficiency in Convolutional Neural Networks
This paper presents a novel approach to network pruning, targeting block pruning in deep neural networks for edge computing environments.
Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels?
Vision-language models such as CLIP learn a generic text-image embedding from large-scale training data.
Self-supervised Video Representation Learning with Cascade Positive Retrieval
Implementation-wise, CPR is complementary to pretext tasks and can be easily applied to previous work.
EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNING
Although CondConv is effective for the performance enhancement of a deep model, it is currently applied to individual tasks only.
Ranked #1 on
Continual Learning
on Flowers (Fine-grained 6 Tasks)
Compacting, Picking and Growing for Unforgetting Continual Learning
First, it can avoid forgetting (i. e., learn new tasks while remembering all previous tasks).
IMMVP: An Efficient Daytime and Nighttime On-Road Object Detector
It is hard to detect on-road objects under various lighting conditions.
