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Found 9 papers, 0 papers with code
DENOISER: Rethinking the Robustness for Open-Vocabulary Action Recognition
The denoised text classes help OVAR models classify visual samples more accurately; in return, classified visual samples help better denoising.
Audio-Visual Segmentation via Unlabeled Frame Exploitation
NFs, temporally adjacent to the labeled frame, often contain rich motion information that assists in the accurate localization of sounding objects.
Audio-aware Query-enhanced Transformer for Audio-Visual Segmentation
The goal of the audio-visual segmentation (AVS) task is to segment the sounding objects in the video frames using audio cues.
Annotation-free Audio-Visual Segmentation
The objective of Audio-Visual Segmentation (AVS) is to localise the sounding objects within visual scenes by accurately predicting pixel-wise segmentation masks.
DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery
However, the challenges exist as there is one structural difference between generative and discriminative models, which limits the direct use.
Constraint and Union for Partially-Supervised Temporal Sentence Grounding
Temporal sentence grounding aims to detect the event timestamps described by the natural language query from given untrimmed videos.
Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization
And as a result, the dual-branch complementarity is effectively fused to promote a strong alliance.
Weakly-supervised Temporal Action Localization
Weakly Supervised Temporal Action Localization
Exploiting Transformation Invariance and Equivariance for Self-supervised Sound Localisation
We present a simple yet effective self-supervised framework for audio-visual representation learning, to localize the sound source in videos.
A 3D Mesh-based Lifting-and-Projection Network for Human Pose Transfer
To leverage the human body shape prior, LPNet exploits the topological information of the body mesh to learn an expressive visual representation for the target person in the 3D mesh space.
