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Found 12 papers, 6 papers with code
Rethinking CLIP-based Video Learners in Cross-Domain Open-Vocabulary Action Recognition
To answer this, we establish a CROSS-domain Open-Vocabulary Action recognition benchmark named XOV-Action, and conduct a comprehensive evaluation of five state-of-the-art CLIP-based video learners under various types of domain gaps.
ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognition
With the proposed ActionHub dataset, we further propose a novel Cross-modality and Cross-action Modeling (CoCo) framework for ZSAR, which consists of a Dual Cross-modality Alignment module and a Cross-action Invariance Mining module.
AdaFocus: Towards End-to-end Weakly Supervised Learning for Long-Video Action Understanding
Under the weak supervision setting, action labels are provided for the whole video without precise start and end times of the action clip.
Ranked #1 on
Long-video Activity Recognition
on Breakfast
Event-Guided Procedure Planning from Instructional Videos with Text Supervision
In this work, we focus on the task of procedure planning from instructional videos with text supervision, where a model aims to predict an action sequence to transform the initial visual state into the goal visual state.
DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition
In this work, we explore effective Vision Transformers to pursue a preferable trade-off between the computational complexity and size of the attended receptive field.
AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection
Critically, in FSDAOD, the data-scarcity in the target domain leads to an extreme data imbalance between the source and target domains, which potentially causes over-adaptation in traditional feature alignment.
Generating Anomalies for Video Anomaly Detection With Prompt-Based Feature Mapping
There also exists a scene gap between virtual and real scenarios, including scene-specific anomalies (events that are abnormal in one scene but normal in another) and scene-specific attributes, such as the viewpoint of the surveillance camera.
Anomaly Detection In Surveillance Videos
Video Anomaly Detection
Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning
Accordingly, we first exclude these surely non-existent categories by a complementary learning loss.
Out-of-distribution Detection by Cross-class Vicinity Distribution of In-distribution Data
We thus improve the discriminability of a pretrained network by finetuning it with out-of-distribution samples drawn from the cross-class vicinity distribution, where each out-of-distribution input corresponds to a complementary label.
Supervision Adaptation Balancing In-distribution Generalization and Out-of-distribution Detection
To tackle this issue, several state-of-the-art methods include adding extra OOD samples to training and assign them with manually-defined labels.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators
According to the Shannon entropy, an energy-based implicit generator is inferred from a discriminator without extra training costs.
Graph-Based High-Order Relation Modeling for Long-Term Action Recognition
In this paper, we propose a Graph-based High-order Relation Modeling (GHRM) module to exploit the high-order relations in the long-term actions for long-term action recognition.
Ranked #5 on
Video Classification
on Breakfast
