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Found 13 papers, 5 papers with code
Plug-and-Play Diffusion Distillation
Furthermore, once trained, our guide model can be applied to various fine-tuned, domain-specific versions of the base diffusion model without the need for additional training: this "plug-and-play" functionality drastically improves inference computation while maintaining the visual fidelity of generated images.
Learning with Capsules: A Survey
The aim of this survey is to provide a comprehensive overview of the capsule network research landscape, which will serve as a valuable resource for the community going forward.
Reformulating Zero-shot Action Recognition for Multi-label Actions
Given a video and a set of action classes, our method predicts a set of confidence scores for each class independently.
Routing with Self-Attention for Multimodal Capsule Networks
We present a new multimodal capsule network that allows us to leverage the strength of capsules in the context of a multimodal learning framework on large amounts of video data.
PLM: Partial Label Masking for Imbalanced Multi-label Classification
By stochastically masking labels during loss computation, the method balances this ratio for each class, leading to improved recall on minority classes and improved precision on frequent classes.
Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
In this paper, we focus on a more relaxed setting: the grounding of relevant visual entities in a weakly supervised manner by training on the VQA task alone.
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos
Multimodal self-supervised learning is getting more and more attention as it allows not only to train large networks without human supervision but also to search and retrieve data across various modalities.
Modeling Multi-Label Action Dependencies for Temporal Action Localization
We propose to improve action localization performance by modeling these action dependencies in a novel attention-based Multi-Label Action Dependency (MLAD)layer.
Ranked #1 on
Action Detection
on Multi-THUMOS
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
The recent research in semi-supervised learning (SSL) is mostly dominated by consistency regularization based methods which achieve strong performance.
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos
For tubelet extraction, we propose a localization network which takes a video clip as input and spatio-temporally detects potential foreground regions at multiple scales to generate action tubelets.
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
In this work we propose a capsule-based approach for semi-supervised video object segmentation.
Multi-modal Capsule Routing for Actor and Action Video Segmentation Conditioned on Natural Language Queries
The existing works on actor-action localization are mainly focused on localization in a single frame instead of the full video.
VideoCapsuleNet: A Simplified Network for Action Detection
In this work, we present a more elegant solution for action detection based on the recently developed capsule network.
