Search Results for author:
Found 15 papers, 3 papers with code
TALK-Act: Enhance Textural-Awareness for 2D Speaking Avatar Reenactment with Diffusion Model
We propose a Motion-Enhanced Textural Alignment module to enhance the bond between driving and target signals.
ReSyncer: Rewiring Style-based Generator for Unified Audio-Visually Synced Facial Performer
Lip-syncing videos with given audio is the foundation for various applications including the creation of virtual presenters or performers.
NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mamba
In addition, we design a traffic representation scheme to extract valid information from massive traffic data while removing biased information.
Teeth-SEG: An Efficient Instance Segmentation Framework for Orthodontic Treatment based on Anthropic Prior Knowledge
Teeth localization, segmentation, and labeling in 2D images have great potential in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health.
LLaMA-Excitor: General Instruction Tuning via Indirect Feature Interaction
LLaMA-Excitor ensures a self-adaptive allocation of additional attention to input instructions, thus effectively preserving LLMs' pre-trained knowledge when fine-tuning LLMs on low-quality instruction-following datasets.
VideoDistill: Language-aware Vision Distillation for Video Question Answering
In this paper, we are inspired by the human recognition and learning pattern and propose VideoDistill, a framework with language-aware (i. e., goal-driven) behavior in both vision perception and answer generation process.
Language-aware Visual Semantic Distillation for Video Question Answering
In this paper we are inspired by the human recognition and learning pattern and propose VideoDistill a framework with language-aware (i. e. goal-driven) behavior in both vision perception and answer generation process.
Teeth-SEG: An Efficient Instance Segmentation Framework for Orthodontic Treatment based on Multi-Scale Aggregation and Anthropic Prior Knowledge
Teeth localization segmentation and labeling in 2D images have great potential in modern dentistry to enhance dental diagnostics treatment planning and population-based studies on oral health.
Building an Invisible Shield for Your Portrait against Deepfakes
Unlike authentic images, where the hidden messages can be extracted with precision, manipulating the facial attributes through deepfake techniques can disrupt the decoding process.
Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption
Specifically, by carefully examining the spatial and temporal properties, we propose to disrupt a real video through a Pseudo-fake Generator and create a wide range of pseudo-fake videos for training.
Delving into Sequential Patches for Deepfake Detection
Recent advances in face forgery techniques produce nearly visually untraceable deepfake videos, which could be leveraged with malicious intentions.
CORE: Consistent Representation Learning for Face Forgery Detection
Specifically, we first capture the different representations with different augmentations, then regularize the cosine distance of the representations to enhance the consistency.
Shallow VAEs with RealNVP Prior Can Perform as Well as Deep Hierarchical VAEs
Using powerful posterior distributions is a popular technique in variational inference.
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder
Using powerful posterior distributions is a popular approach to achieving better variational inference.
Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e. g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation.
