Alternatives and similar repositories for hierarcaps:

Users that are interested in hierarcaps are comparing it to the libraries listed below

• linzhiqiu / visual_gpt_score
  VisualGPTScore for visio-linguistic reasoning
  ☆26Updated last year
• RAIVNLab / CREPE
  [CVPR23 Highlight] CREPE: Can Vision-Language Foundation Models Reason Compositionally?
  ☆32Updated last year
• ExplainableML / flair
  ☆26Updated this week
• naver-ai / prolip
  ☆36Updated this week
• Zi-hao-Wei / Efficient-Vision-Language-Pre-training-by-Cluster-Masking
  [CVPR 2024] Improving language-visual pretraining efficiency by perform cluster-based masking on images.
  ☆25Updated 8 months ago
• tripletclip / TripletCLIP
  [NeurIPS 2024] Official PyTorch implementation of "Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives"
  ☆33Updated last month
• ninatu / howtocaption
  Official implementation of "HowToCaption: Prompting LLMs to Transform Video Annotations at Scale." ECCV 2024
  ☆50Updated 3 months ago
• amitakamath / whatsup_vlms
  Code and datasets for "What’s “up” with vision-language models? Investigating their struggle with spatial reasoning".
  ☆38Updated 11 months ago
• ExplainableML / EgoCVR
  [ECCV 2024] EgoCVR: An Egocentric Benchmark for Fine-Grained Composed Video Retrieval
  ☆33Updated 5 months ago
• showlab / datacentric.vlp
  Compress conventional Vision-Language Pre-training data
  ☆49Updated last year
• McGill-NLP / diffusion-itm
  Code and data setup for the paper "Are Diffusion Models Vision-and-language Reasoners?"
  ☆31Updated 10 months ago
• vinid / neg_clip
  NegCLIP.
  ☆30Updated last year
• showlab / MovieSeq
  [ECCV2024] Learning Video Context as Interleaved Multimodal Sequences
  ☆35Updated last week
• dhg-wei / TOPA
  (NeurIPS 2024 Spotlight) TOPA: Extend Large Language Models for Video Understanding via Text-Only Pre-Alignment
  ☆26Updated 4 months ago
• ytaek-oh / fsc-clip
  [EMNLP 2024] Preserving Multi-Modal Capabilities of Pre-trained VLMs for Improving Vision-Linguistic Compositionality
  ☆15Updated 3 months ago
• ytaek-oh / vl_compo
  ☆11Updated 6 months ago
• xvjiarui / IMProv
  IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks
  ☆59Updated 4 months ago
• ys-zong / VL-ICL
  [ICLR 2025] VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning
  ☆35Updated this week
• see-say-segment / sesame
  🔥 [CVPR 2024] Official implementation of "See, Say, and Segment: Teaching LMMs to Overcome False Premises (SESAME)"
  ☆32Updated 7 months ago
• snumprlab / isr-dpo
  ISR-DPO:Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO
  ☆13Updated 2 weeks ago
• ExplainableML / ImageSelect
  Code for the paper "If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection"
  ☆27Updated last year
• arijitray1993 / COLA
  COLA: Evaluate how well your vision-language model can Compose Objects Localized with Attributes!
  ☆24Updated 2 months ago
• Lizw14 / Super-CLEVR
  Code for paper "Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning"
  ☆23Updated last year
• ExplainableML / DataDream
  [ECCV 2024] Official repository for "DataDream: Few-shot Guided Dataset Generation"
  ☆29Updated 6 months ago
• ExplainableML / WaffleCLIP
  Official repository for the ICCV 2023 paper: "Waffling around for Performance: Visual Classification with Random Words and Broad Concepts…
  ☆56Updated last year
• orrzohar / LOVM
  [NeurIPS 2023] Official Pytorch code for LOVM: Language-Only Vision Model Selection
  ☆20Updated 11 months ago
• Shengcao-Cao / groundLMM
  Emerging Pixel Grounding in Large Multimodal Models Without Grounding Supervision
  ☆29Updated 3 months ago
• KHU-VLL / DEVIAS
  [ECCV 2024 Oral] Official implementation of the paper "DEVIAS: Learning Disentangled Video Representations of Action and Scene"
  ☆15Updated 3 months ago
• jaehong31 / SAFREE
  [ICLR 2025] SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image and Video Generation
  ☆21Updated last week
• amitakamath / vl_text_encoders_are_bottlenecks
  Code and datasets for "Text encoders are performance bottlenecks in contrastive vision-language models". Coming soon!
  ☆11Updated last year