Revisiting the domain shift and sample uncertainty in multi-source active domain transfer
Abstract Active Domain Adaptation (ADA) aims to maximally boost model adaptation in a
new target domain by actively selecting a limited number of target data to annotate. This …
new target domain by actively selecting a limited number of target data to annotate. This …
Are binary annotations sufficient? video moment retrieval via hierarchical uncertainty-based active learning
Recent research on video moment retrieval has mostly focused on enhancing the
performance of accuracy, efficiency, and robustness, all of which largely rely on the …
performance of accuracy, efficiency, and robustness, all of which largely rely on the …
Panoptic scene graph generation with semantics-prototype learning
Panoptic Scene Graph Generation (PSG) parses objects and predicts their relationships
(predicate) to connect human language and visual scenes. However, different language …
(predicate) to connect human language and visual scenes. However, different language …
Intelligent model update strategy for sequential recommendation
Modern online platforms are increasingly employing recommendation systems to address
information overload and improve user engagement. There is an evolving paradigm in this …
information overload and improve user engagement. There is an evolving paradigm in this …
Gradient-regulated meta-prompt learning for generalizable vision-language models
Prompt tuning, a recently emerging paradigm, enables the powerful vision-language pre-
training models to adapt to downstream tasks in a parameter-and data-efficient way, by …
training models to adapt to downstream tasks in a parameter-and data-efficient way, by …
Multi-modal action chain abductive reasoning
M Li, T Wang, J Xu, K Han, S Zhang… - Proceedings of the …, 2023 - aclanthology.org
Abductive Reasoning, has long been considered to be at the core ability of humans, which
enables us to infer the most plausible explanation of incomplete known phenomena in daily …
enables us to infer the most plausible explanation of incomplete known phenomena in daily …
Hig: Hierarchical interlacement graph approach to scene graph generation in video understanding
Visual interactivity understanding within visual scenes presents a significant challenge in
computer vision. Existing methods focus on complex interactivities while leveraging a simple …
computer vision. Existing methods focus on complex interactivities while leveraging a simple …
Learning in imperfect environment: Multi-label classification with long-tailed distribution and partial labels
Conventional multi-label classification (MLC) methods assume that all samples are fully
labeled and identically distributed. Unfortunately, this assumption is unrealistic in large …
labeled and identically distributed. Unfortunately, this assumption is unrealistic in large …
Efficient long-short temporal attention network for unsupervised video object segmentation
Abstract Unsupervised Video Object Segmentation (VOS) aims at identifying the contours of
primary foreground objects in videos without any prior knowledge. However, previous …
primary foreground objects in videos without any prior knowledge. However, previous …
Unsupervised domain adaptation for video object grounding with cascaded debiasing learning
This paper addresses the Unsupervised Domain Adaptation (UDA) for the dense frame
prediction task-Video Object Grounding (VOG). This investigation springs from the …
prediction task-Video Object Grounding (VOG). This investigation springs from the …