Search Results for author:
Found 14 papers, 4 papers with code
F3A-GAN: Facial Flow for Face Animation with Generative Adversarial Networks
Formulated as a conditional generation problem, face animation aims at synthesizing continuous face images from a single source image driven by a set of conditional face motion.
Multitask Identity-Aware Image Steganography via Minimax Optimization
The key issue of the direct recognition is to preserve identity information of secret images into container images and make container images look similar to cover images at the same time.
VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation
To diversify the extrinsic factors of gait, we build a complicated scene with a dense camera layout.
Recent Advances and Trends in Multimodal Deep Learning: A Review
Deep Learning has implemented a wide range of applications and has become increasingly popular in recent years.
Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion
In principle, the feature modeling scheme is carried out in a depth-sensitive attention module, which leads to the RGB feature enhancement as well as the background distraction reduction by capturing the depth geometry prior.
Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning
Unsupervised domain adaptation (UDA) typically carries out knowledge transfer from a label-rich source domain to an unlabeled target domain by adversarial learning.
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios
With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, which consists of around one million silhouette sequences of 11, 000 subjects with fine-grained attributes in various complicated scenarios.
RDI-Net: Relational Dynamic Inference Networks
In this paper, we model the relations for dynamic inference from two aspects: the routers and the samples.
ResKD: Residual-Guided Knowledge Distillation
In this paper, we see knowledge distillation in a fresh light, using the knowledge gap, or the residual, between a teacher and a student as guidance to train a much more lightweight student, called a res-student.
CoDiNet: Path Distribution Modeling with Consistency and Diversity for Dynamic Routing
In this paper, we see dynamic routing networks in a fresh light, formulating a routing method as a mapping from a sample space to a routing space.
Tamed Warping Network for High-Resolution Semantic Video Segmentation
Based on the feature fusion, our Context Feature Rectification~(CFR) module learns the model's difference from a per-frame model to correct the warped features.
Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation
To satisfy the stringent requirements on computational resources in the field of real-time semantic segmentation, most approaches focus on the hand-crafted design of light-weight segmentation networks.
Neural Architecture Search
Real-Time Semantic Segmentation
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BANet: Bidirectional Aggregation Network with Occlusion Handling for Panoptic Segmentation
Panoptic segmentation aims to perform instance segmentation for foreground instances and semantic segmentation for background stuff simultaneously.
TapLab: A Fast Framework for Semantic Video Segmentation Tapping into Compressed-Domain Knowledge
Real-time semantic video segmentation is a challenging task due to the strict requirements of inference speed.
