https://github.com/phoenixz810/mg-llava
공식 코드MG-LLaVA: Towards Multi-Granularity Visual Instruction Tuning
Papers with Code 아카이브
Visual Question Answering
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pickxiguapi/embodied-fsd
공식 코드From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
https://github.com/pjlab-adg/gpt4v-ad-exploration
공식 코드On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving
https://github.com/pku-icst-mipl/finedefics_iclr2025
공식 코드https://github.com/polymathbenchmark/PolyMATH
공식 코드Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmark
https://github.com/pramodkaushik/acl18_results
공식 코드https://github.com/prdwb/okvqa-release
공식 코드Passage Retrieval for Outside-Knowledge Visual Question Answering
https://github.com/premsrit/SPARTUNQChain
공식 코드https://github.com/princeton-pli/vlm_s2h
공식 코드Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?
https://github.com/princeton-vl/SpatialSense
공식 코드SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition
https://github.com/princeton-vl/uniqa-3d
공식 코드https://github.com/princetonvisualai/pointingqa
공식 코드Point and Ask: Incorporating Pointing into Visual Question Answering
https://github.com/prithv1/cvpr2017_counting
공식 코드https://github.com/promptslab/rosettaeval
공식 코드https://github.com/protagolabs/SpatialEval
공식 코드https://github.com/psudslab/FEDMEKI
공식 코드FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection
https://github.com/pudumagico/kr2024
공식 코드Declarative Knowledge Distillation from Large Language Models for Visual Question Answering Datasets
https://github.com/pzyseere/metaspatial
공식 코드MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse
https://github.com/q-future/visual-question-answering-for-video-quality-assessment
공식 코드VQA$^2$: Visual Question Answering for Video Quality Assessment
https://github.com/qhnhynmm/viocrvqa
공식 코드https://github.com/qiantianwen/nuscenes-qa
공식 코드NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario
https://github.com/qingzwang/GHA-ImageCaptioning
공식 코드https://github.com/qizhust/cmcl_vqa_pl
공식 코드Cross-Modal Contrastive Learning for Robust Reasoning in VQA
https://github.com/quiil/quiil_thompson_solution
공식 코드https://github.com/qwenlm/qwen-vl
공식 코드Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
https://github.com/qwenlm/qwen2-vl
공식 코드Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
https://github.com/qybc/medblip
공식 코드MedBLIP: Bootstrapping Language-Image Pre-training from 3D Medical Images and Texts
https://github.com/rabiulcste/vqazero
공식 코드Investigating Prompting Techniques for Zero- and Few-Shot Visual Question Answering
https://github.com/rajatkoner08/Graphhopper
공식 코드Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question Answering
https://github.com/rajeswar18/pix2shape
공식 코드Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation
https://github.com/ramprs/grad-cam
공식 코드Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/rbler1234/ost-bench
공식 코드OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding
https://github.com/reallm-labs/infigui-r1
공식 코드InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners
https://github.com/reml-group/alo
공식 코드https://github.com/reml-group/fortisavqa
공식 코드FortisAVQA and MAVEN: a Benchmark Dataset and Debiasing Framework for Robust Multimodal Reasoning
https://github.com/reml-group/music-avqa-r
공식 코드Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.