Search Results for author:
Found 24 papers, 6 papers with code
DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Sampling
Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors.
Semantics, Distortion, and Style Matter: Towards Source-free UDA for Panoramic Segmentation
However, the distinct projection discrepancies between source and target domains impede the direct knowledge transfer; thus, we propose a panoramic prototype adaptation module (PPAM) to integrate panoramic prototypes from the extracted knowledge for adaptation.
Dream360: Diverse and Immersive Outdoor Virtual Scene Creation via Transformer-Based 360 Image Outpainting
To this end, we propose a transformer-based 360 image outpainting framework called Dream360, which can generate diverse, high-fidelity, and high-resolution panoramas from user-selected viewports, considering the spherical properties of 360 images.
Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise
Neural radiance fields (NeRF) have been proposed as an innovative 3D representation method.
2D-Guided 3D Gaussian Segmentation
Recently, 3D Gaussian, as an explicit 3D representation method, has demonstrated strong competitiveness over NeRF (Neural Radiance Fields) in terms of expressing complex scenes and training duration.
FedMKGC: Privacy-Preserving Federated Multilingual Knowledge Graph Completion
As such, the aggregated language model can leverage complementary knowledge from multilingual KGs without demanding raw user data sharing.
Take History as a Mirror in Heterogeneous Federated Learning
Federated Learning (FL) allows several clients to cooperatively train machine learning models without disclosing the raw data.
Viewport Prediction for Volumetric Video Streaming by Exploring Video Saliency and Trajectory Information
To our knowledge, this is the first comprehensive study of viewport prediction in volumetric video streaming.
Distilling Efficient Vision Transformers from CNNs for Semantic Segmentation
Due to the completely different characteristics of ViT and CNN and the long-existing capacity gap between teacher and student models in Knowledge Distillation (KD), directly transferring the cross-model knowledge is non-trivial.
NLPBench: Evaluating Large Language Models on Solving NLP Problems
Recent developments in large language models (LLMs) have shown promise in enhancing the capabilities of natural language processing (NLP).
Detect Depression from Social Networks with Sentiment Knowledge Sharing
Social network plays an important role in propagating people's viewpoints, emotions, thoughts, and fears.
Spatiotemporal and Semantic Zero-inflated Urban Anomaly Prediction
Urban anomaly predictions, such as traffic accident prediction and crime prediction, are of vital importance to smart city security and maintenance.
Unleashing ChatGPT on the Metaverse: Savior or Destroyer?
The incorporation of artificial intelligence (AI) technology, and in particular natural language processing (NLP), is becoming increasingly vital for the development of immersive and interactive metaverse experiences.
TKN: Transformer-based Keypoint Prediction Network For Real-time Video Prediction
Video prediction is a complex time-series forecasting task with great potential in many use cases.
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection
In particular, a global generator is used to extract the knowledge of global data distribution and distill it into each client's local model.
Mitigating Backdoors in Federated Learning with FLD
Federated learning allows clients to collaboratively train a global model without uploading raw data for privacy preservation.
Celeritas: Fast Optimizer for Large Dataflow Graphs
The rapidly enlarging neural network models are becoming increasingly challenging to run on a single device.
Federated Split GANs
Mobile devices and the immense amount and variety of data they generate are key enablers of machine learning (ML)-based applications.
HideNseek: Federated Lottery Ticket via Server-side Pruning and Sign Supermask
Consequently, the training requires high computation cost and a long time to converge while the model performance does not pay off.
Towards User-Centered Metrics for Trustworthy AI in Immersive Cyberspace
AI plays a key role in current cyberspace and future immersive ecosystems that pinpoint user experiences.
Loss Tolerant Federated Learning
Federated learning has attracted attention in recent years for collaboratively training data on distributed devices with privacy-preservation.
DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoV
To this end, we propose a Decentralized Reinforcement Learning at the Edge for traffic light control in the IoV (DRLE).
Multipath Computation Offloading for Mobile Augmented Reality
With only 70% WiFi availability, our system keeps the excess latency below 9 ms. We finally evaluate the capabilities of the upcoming 5G and 802. 11ax
