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Found 9 papers, 1 papers with code
BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering
Developing blind video deflickering (BVD) algorithms to enhance video temporal consistency, is gaining importance amid the flourish of image processing and video generation.
Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis
Recent works in implicit representations, such as Neural Radiance Fields (NeRF), have advanced the generation of realistic and animatable head avatars from video sequences.
General Method for Solving Four Types of SAT Problems
We experimentally verify that this paradigm can prune the unnecessary search space to find the optimal Boolean assignments for the problem.
DiffBFR: Bootstrapping Diffusion Model Towards Blind Face Restoration
This design is implemented with two key components: 1) Identity Restoration Module (IRM) for preserving the face details in results.
StyO: Stylize Your Face in Only One-Shot
And it introduces a novel triple reconstruction loss to fine-tune the pre-trained LDM for encoding style and content into corresponding identifiers; 2) Fine-grained Content Controller (FCC) for the recombination phase.
DropKey for Vision Transformer
Given exploration on the above three questions, we present the novel DropKey method that regards Key as the drop unit and exploits decreasing schedule for drop ratio, improving ViTs in a general way.
Masked Reconstruction Contrastive Learning with Information Bottleneck Principle
In order to alleviate the discriminative information overfitting problem effectively, we employ the reconstruction task to regularize the discriminative task.
Ranked #23 on
Self-Supervised Image Classification
on ImageNet
Contrastive Learning
Self-Supervised Image Classification
+2
DropKey
Given exploration on the above three questions, we present the novel DropKey method that regards Key as the drop unit and exploits decreasing schedule for drop ratio, improving ViTs in a general way.
DFS: A Diverse Feature Synthesis Model for Generalized Zero-Shot Learning
In this paper, we propose to enhance the generalizability of GZSL models via improving feature diversity of unseen classes.
