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Found 11 papers, 2 papers with code
Marine Saliency Segmenter: Object-Focused Conditional Diffusion with Region-Level Semantic Knowledge Distillation
Marine Saliency Segmentation (MSS) plays a pivotal role in various vision-based marine exploration tasks.
VLA-Cache: Towards Efficient Vision-Language-Action Model via Adaptive Token Caching in Robotic Manipulation
A natural idea is to reuse the computational results of unchanged visual tokens from the last step.
AI Scaling: From Up to Down and Out
It argues that while Scaling Up of models faces inherent bottlenecks, the future trajectory of AI scaling lies in Scaling Down and Scaling Out.
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration
For the sacrificed image details caused by underwater scattering, we further present the Cross-Spectral Detail Refinement (CSDR) to enhance the high-frequency details, which are integrated with the low-frequency signal as input conditions for guiding the diffusion.
FusionSAM: Latent Space driven Segment Anything Model for Multimodal Fusion and Segmentation
In this paper, we introduce SAM into multimodal image segmentation for the first time, proposing a novel framework that combines Latent Space Token Generation (LSTG) and Fusion Mask Prompting (FMP) modules to enhance SAM's multimodal fusion and segmentation capabilities.
Collage Prompting: Budget-Friendly Visual Recognition with GPT-4V
Based on the observation that the accuracy of GPT-4V's image recognition varies significantly with the order of images within the collage prompt, our method further learns to optimize the arrangement of images for maximum recognition accuracy.
Visual Imitation Learning with Calibrated Contrastive Representation
Adversarial Imitation Learning (AIL) allows the agent to reproduce expert behavior with low-dimensional states and actions.
MAEDiff: Masked Autoencoder-enhanced Diffusion Models for Unsupervised Anomaly Detection in Brain Images
To address these two issues, we propose a novel Masked Autoencoder-enhanced Diffusion Model (MAEDiff) for unsupervised anomaly detection in brain images.
Imitation Learning from Purified Demonstrations
In the first step, we apply a forward diffusion process to smooth potential noises in imperfect demonstrations by introducing additional noise.
Unlabeled Imperfect Demonstrations in Adversarial Imitation Learning
The trajectories of an initial agent policy could be closer to those non-optimal expert demonstrations, but within the framework of adversarial imitation learning, agent policy will be optimized to cheat the discriminator and produce trajectories that are similar to those optimal expert demonstrations.
Multi-Tailed Vision Transformer for Efficient Inference
To satisfy the sequential input of Transformer, the tail of ViT first splits each image into a sequence of visual tokens with a fixed length.
