https://github.com/Dod-o/VT-SSum
공식 코드VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
What is Human Pose Estimation? Human pose estimation is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years. The reason for its importance is the abundance of applications that can benefit from such a technology. For example, human pose estimation allows for higher-level reasoning in the context of human-computer interaction and activity recognition; it is also one of the basic building blocks for marker-less motion capture (MoCap) technology. MoCap technology is useful for applications ranging from character animation to clinical analysis of gait pathologies.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization
CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior
Delving into the Utilisation of ChatGPT in Scientific Publications in Astronomy
Decoding MIE: A Novel Dataset Approach Using Topic Extraction and Affiliation Parsing
XFORMAL: A Benchmark for Multilingual Formality Style Transfer
Empowering Meta-Analysis: Leveraging Large Language Models for Scientific Synthesis
Diversified Arbitrary Style Transfer via Deep Feature Perturbation
GLStyleNet: Higher Quality Style Transfer Combining Global and Local Pyramid Features
FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving
FaceFormer: Speech-Driven 3D Facial Animation with Transformers
BillSum: A Corpus for Automatic Summarization of US Legislation
Visual News: Benchmark and Challenges in News Image Captioning
GECTurk: Grammatical Error Correction and Detection Dataset for Turkish
Frustratingly Simple Domain Generalization via Image Stylization
No perspective, no perception!! Perspective-aware Healthcare Answer Summarization
SLEDGE: A Simple Yet Effective Baseline for COVID-19 Scientific Knowledge Search
LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models
TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition
ICECAP: Information Concentrated Entity-aware Image Captioning
Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.