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Found 8 papers, 1 papers with code
Query-Based Knowledge Sharing for Open-Vocabulary Multi-Label Classification
Identifying labels that did not appear during training, known as multi-label zero-shot learning, is a non-trivial task in computer vision.
Text as Image: Learning Transferable Adapter for Multi-Label Classification
Pre-trained vision-language models have notably accelerated progress of open-world concept recognition.
Beyond Visual Cues: Synchronously Exploring Target-Centric Semantics for Vision-Language Tracking
However, current VL trackers have not fully exploited the power of VL learning, as they suffer from limitations such as heavily relying on off-the-shelf backbones for feature extraction, ineffective VL fusion designs, and the absence of VL-related loss functions.
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift
This paper addresses this fundamental question by proving that, surprisingly, classical Maximum Likelihood Estimation (MLE) purely using source data (without any modification) achieves the minimax optimality for covariate shift under the well-specified setting.
UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation
Uncertainty quantification for prediction is an intriguing problem with significant applications in various fields, such as biomedical science, economic studies, and weather forecasts.
On the Provable Advantage of Unsupervised Pretraining
Unsupervised pretraining, which learns a useful representation using a large amount of unlabeled data to facilitate the learning of downstream tasks, is a critical component of modern large-scale machine learning systems.
Scene-Aware Label Graph Learning for Multi-Label Image Classification
Multi-label image classification refers to assigning a set of labels for an image.
Two-Stream Transformer for Multi-Label Image Classification
Specifically, in each layer of TSFormer, a cross-modal attention module is developed to aggregate visual features from spatial stream into semantic stream and update label semantics via a residual connection.
