conftrace_

vision-language model

2348 papers

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Also known as

VLM VL MODEL VLMS

Co-occurring keywords

multimodal learning (4645) zero-shot learning (3650) vision language model (767) contrastive learning (4032) large language model (13587) visual question answering (1017) transfer learning (5449) few-shot learning (3398) knowledge distillation (3725) semantic segmentation (3186)

Papers

Autoregressive Omni-Aware Outpainting for Open-Vocabulary 360-Degree Image Generation AAAI 2024
DART: Dual-Modal Adaptive Online Prompting and Knowledge Retention for Test-Time Adaptation AAAI 2024
Relax Image-Specific Prompt Requirement in SAM: A Single Generic Prompt for Segmenting Camouflaged Objects AAAI 2024
Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior AAAI 2024
Déjà Vu Memorization in Vision–Language Models NIPS 2024
MemVLT: Vision-Language Tracking with Adaptive Memory-based Prompts NIPS 2024
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples NIPS 2024
Easy Regional Contrastive Learning of Expressive Fashion Representations NIPS 2024
A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks NIPS 2024
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation NIPS 2024
WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences NIPS 2024
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning NIPS 2024
LG-CAV: Train Any Concept Activation Vector with Language Guidance NIPS 2024
SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge NIPS 2024
CLIPCEIL: Domain Generalization through CLIP via Channel rEfinement and Image-text aLignment NIPS 2024
Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model NIPS 2024
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions NIPS 2024
FineCLIP: Self-distilled Region-based CLIP for Better Fine-grained Understanding NIPS 2024
Bridge the Modality and Capability Gaps in Vision-Language Model Selection NIPS 2024
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control NIPS 2024
Domain Adaptation for Large-Vocabulary Object Detectors NIPS 2024
GuardT2I: Defending Text-to-Image Models from Adversarial Prompts NIPS 2024
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection NIPS 2024
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models NIPS 2024
What matters when building vision-language models? NIPS 2024