https://github.com/furkanbiten/object-bias
공식 코드Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning
Papers with Code 아카이브
Image Captioning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 8
- 평가표
- 34
- 보존된 평가 기록
- 419
Image Captioning is the task of describing the content of an image in words. This task lies at the intersection of computer vision and natural language processing. Most image captioning systems use an encoder-decoder framework, where an input image is encoded into an intermediate representation of the information in the image, and then decoded into a descriptive text sequence. The most popular benchmarks are nocaps and COCO, and models are typically evaluated according to a BLEU or CIDER metric.
( Image credit: Reflective Decoding Network for Image Captioning, ICCV'19)
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fy-vision/diga
공식 코드DiGA: Distil to Generalize and then Adapt for Domain Adaptive Semantic Segmentation
https://github.com/gabrielsantosrv/PraCegoVer
공식 코드#PraCegoVer: A Large Dataset for Image Captioning in Portuguese
https://github.com/gallenszl/ucfnet
공식 코드Digging Into Uncertainty-based Pseudo-label for Robust Stereo Matching
https://github.com/garyjiajia/tsg
공식 코드https://github.com/gautierevn/blip2idc
공식 코드Reframing Image Difference Captioning with BLIP2IDC and Synthetic Augmentation
https://github.com/gautierevn/swift_watermarking
공식 코드https://github.com/gchochla/vault
공식 코드VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media
https://github.com/gcyzsl/cvlmn
공식 코드Learning to Collocate Visual-Linguistic Neural Modules for Image Captioning
https://github.com/gecgomes/Multilingual_IC_Eval
공식 코드Evaluation of Multilingual Image Captioning: How far can we get with CLIP models?
https://github.com/gfmei/softclu
공식 코드Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding
https://github.com/ghostish/open3dsot
공식 코드An Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
https://github.com/gist-ailab/domain-specific-block-selection-and-paired-view-pseudo-labeling-for-online-tta
공식 코드Domain-Specific Block Selection and Paired-View Pseudo-Labeling for Online Test-Time Adaptation
https://github.com/gistvision/psvl
공식 코드https://github.com/gjwubyron/icu
공식 코드https://github.com/gofigure-lanl/figure-segmentation
공식 코드DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding
https://github.com/google-deepmind/semppl
공식 코드SemPPL: Predicting pseudo-labels for better contrastive representations
https://github.com/google-research-datasets/Image-Caption-Quality-Dataset
공식 코드Quality Estimation for Image Captions Based on Large-scale Human Evaluations
https://github.com/google-research-datasets/T2-Guiding
공식 코드Understanding Guided Image Captioning Performance across Domains
https://github.com/google-research-datasets/conceptual-12m
공식 코드Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
https://github.com/google-research-datasets/maverics
공식 코드https://github.com/google-research-datasets/wit
공식 코드https://github.com/google-research-datasets/wit/blob/main/wikiweb2m.md
공식 코드A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding
https://github.com/google-research/big_vision
공식 코드https://github.com/google-research/fixmatch
공식 코드FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
https://github.com/google-research/google-research/tree/master/socraticmodels
공식 코드Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
https://github.com/google-research/language
공식 코드https://github.com/google-research/pix2seq
공식 코드https://github.com/google-research/pix2struct
공식 코드Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
https://github.com/google-research/scenic/tree/main/scenic/projects/knowledge_visual_language
공식 코드https://github.com/google-research/syn-rep-learn
공식 코드Learning Vision from Models Rivals Learning Vision from Data
https://github.com/google/localized-narratives
공식 코드https://github.com/google/tim-gan
공식 코드Text as Neural Operator: Image Manipulation by Text Instruction
https://github.com/gorilla-lab-scut/ttac
공식 코드Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering
https://github.com/gpantaz/probing-resamplers
공식 코드Lost in Space: Probing Fine-grained Spatial Understanding in Vision and Language Resamplers
https://github.com/gregor-ge/mblip
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.