https://github.com/jayparanjape/f-vita
공식 코드F-ViTA: Foundation Model Guided Visible to Thermal Translation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
F-ViTA: Foundation Model Guided Visible to Thermal Translation
RepVF: A Unified Vector Fields Representation for Multi-task 3D Perception
Anchor-free Oriented Proposal Generator for Object Detection
CrossKD: Cross-Head Knowledge Distillation for Object Detection
SelfRecon: Self Reconstruction Your Digital Avatar from Monocular Video
Exploiting News Article Structure for Automatic Corpus Generation of Entailment Datasets
Localization of Fake News Detection via Multitask Transfer Learning
DenseCap: Fully Convolutional Localization Networks for Dense Captioning
Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation
Pattern-based Acquisition of Scientific Entities from Scholarly Article Titles
Computer Science Named Entity Recognition in the Open Research Knowledge Graph
Bringing Generalization to Deep Multi-View Pedestrian Detection
NeRF-Loc: Visual Localization with Conditional Neural Radiance Field
MedleyVox: An Evaluation Dataset for Multiple Singing Voices Separation
Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
PolyIE: A Dataset of Information Extraction from Polymer Material Scientific Literature
DRRNet: Macro-Micro Feature Fusion and Dual Reverse Refinement for Camouflaged Object Detection
Law Article-Enhanced Legal Case Matching: a Causal Learning Approach
Where are we in audio deepfake detection? A systematic analysis over generative and detection models
Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection
T-FFTRadNet: Object Detection with Swin Vision Transformers from Raw ADC Radar Signals
An Embedded Monocular Vision Approach for Ground-Aware Objects Detection and Position Estimation
Generative Sparse Detection Networks for 3D Single-shot Object Detection
Collaborative Transformers for Grounded Situation Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.