Search Results for author:
Found 12 papers, 7 papers with code
Generative Active Learning for Image Synthesis Personalization
The primary challenge in conducting active learning on generative models lies in the open-ended nature of querying, which differs from the closed form of querying in discriminative models that typically target a single concept.
BronchoTrack: Airway Lumen Tracking for Branch-Level Bronchoscopic Localization
Localizing the bronchoscope in real time is essential for ensuring intervention quality.
Compositional Inversion for Stable Diffusion Models
It stems from the fact that during inversion, the irrelevant semantics in the user images are also encoded, forcing the inverted concepts to occupy locations far from the core distribution in the embedding space.
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific Narratives
Learning scene graphs from natural language descriptions has proven to be a cheap and promising scheme for Scene Graph Generation (SGG).
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and Retention
For the more challenging settings of relation-involved open vocabulary SGG, the proposed approach integrates relation-aware pre-training utilizing image-caption data and retains visual-concept alignment through knowledge distillation.
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.
SurgPLAN: Surgical Phase Localization Network for Phase Recognition
To address these two challenges, we propose a Surgical Phase LocAlization Network, named SurgPLAN, to facilitate a more accurate and stable surgical phase recognition with the principle of temporal detection.
PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical Instruments
To address this issue, we propose a novel yet effective weakly-supervised surgical instrument instance segmentation approach, named Point-based Weakly-supervised Instance Segmentation (PWISeg).
WS-YOLO: Weakly Supervised Yolo Network for Surgical Tool Localization in Endoscopic Videos
Being able to automatically detect and track surgical instruments in endoscopic video recordings would allow for many useful applications that could transform different aspects of surgery.
Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search
On the other hand, the similarity of cross-scale images is often smaller than that of images with the same scale for a person, which will increase the difficulty of matching.
Second-Order Global Attention Networks for Graph Classification and Regression
Graph Neural Networks (GNNs) are powerful to learn representation of graph-structured data, which fuse both attributive and topological information.
Unsupervised Graph Association for Person Re-Identification
By doing this, we can learn view-invariant representation for all person.
