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Found 6 papers, 0 papers with code
Simultaneously Short- and Long-Term Temporal Modeling for Semi-Supervised Video Semantic Segmentation
In this work, we propose a novel feature enhancement network to simultaneously model short- and long-term temporal correlation.
Training Object Detectors From Scratch: An Empirical Study in the Era of Vision Transformer
Instead of proposing a specific vision transformer based detector, in this work, our goal is to reveal the insights of training vision transformer based detectors from scratch.
LPSNet: A Lightweight Solution for Fast Panoptic Segmentation
Panoptic segmentation is a challenging task aiming to simultaneously segment objects (things) at instance level and background contents (stuff) at semantic level.
Deep Reinforcement Learning with Label Embedding Reward for Supervised Image Hashing
Deep hashing has shown promising results in image retrieval and recognition.
Conditional Generative Adversarial Network for Structured Domain Adaptation
In recent years, deep neural nets have triumphed over many computer vision problems, including semantic segmentation, which is a critical task in emerging autonomous driving and medical image diagnostics applications.
Fried Binary Embedding for High-Dimensional Visual Features
We argue that long binary codes (b O(d)) are critical to fully utilize the discriminative power of high-dimensional visual features, and can achieve better results in various tasks such as approximate nearest neighbour search.
