Search Results for author:
Found 18 papers, 12 papers with code
LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection
Explainable fake news detection predicts the authenticity of news items with annotated explanations.
DTFormer: A Transformer-Based Method for Discrete-Time Dynamic Graph Representation Learning
Discrete-Time Dynamic Graphs (DTDGs), which are prevalent in real-world implementations and notable for their ease of data acquisition, have garnered considerable attention from both academic researchers and industry practitioners.
Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling
These works can generate temporal node representations by encoding the surrounding neighborhoods for the target node.
Prompt Learning on Temporal Interaction Graphs
In detail, we propose a temporal prompt generator to offer temporally-aware prompts for different tasks.
RoHM: Robust Human Motion Reconstruction via Diffusion
We apply RoHM to a variety of tasks -- from motion reconstruction and denoising to spatial and temporal infilling.
EgoGen: An Egocentric Synthetic Data Generator
To address this challenge, we introduce EgoGen, a new synthetic data generator that can produce accurate and rich ground-truth training data for egocentric perception tasks.
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation
To overcome the indiscriminate updating issue, we introduce the Adaptive Short-term Updater module that will automatically discard the useless or noisy edges, ensuring iLoRE's effectiveness and instant ability.
RDGSL: Dynamic Graph Representation Learning with Structure Learning
To address the noise dynamics issue, we introduce the Dynamic Graph Filter, where we innovatively propose a dynamic noise function that dynamically captures both current and historical noise, enabling us to assess the temporal aspect of noise and generate a denoised graph.
SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding
Simultaneously, resource consumption of a single-GPU can be diminished by up to 69%, thus enabling the multiple GPU-based training and acceleration encompassing millions of nodes and billions of edges.
POV-Surgery: A Dataset for Egocentric Hand and Tool Pose Estimation During Surgical Activities
The surgical usage of Mixed Reality (MR) has received growing attention in areas such as surgical navigation systems, skill assessment, and robot-assisted surgeries.
Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric Views
One of the biggest challenges of this task is severe body truncation due to close social distances in egocentric scenarios, which brings large pose ambiguities for unseen body parts.
SAGA: Stochastic Whole-Body Grasping with Contact
Given an initial pose and the generated whole-body grasping pose as the start and end of the motion respectively, we design a novel contact-aware generative motion infilling module to generate a diverse set of grasp-oriented motions.
EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devices
Key to reasoning about interactions is to understand the body pose and motion of the interaction partner from the egocentric view.
Learning Motion Priors for 4D Human Body Capture in 3D Scenes
To prove the effectiveness of the proposed motion priors, we combine them into a novel pipeline for 4D human body capture in 3D scenes.
Facial Emotion Recognition with Noisy Multi-task Annotations
In our formulation, we exploit a new method to enable the emotion prediction and the joint distribution learning in a unified adversarial learning game.
PLACE: Proximity Learning of Articulation and Contact in 3D Environments
To synthesize realistic human-scene interactions, it is essential to effectively represent the physical contact and proximity between the body and the world.
Neural Architecture Search as Sparse Supernet
This paper aims at enlarging the problem of Neural Architecture Search (NAS) from Single-Path and Multi-Path Search to automated Mixed-Path Search.
One-shot Face Reenactment
However, in real-world scenario end-users often only have one target face at hand, rendering existing methods inapplicable.
