Image segmentation in robotics is an ongoing research field in which neural networks have shown promising performance. In this paper, we introduce MapSegNet, a deep convolutional neural network for ...

ViCA2 Architecture Dual Vision Encoders Token Ratio Control Specialized Datasets for Visuospatial Cognition Training Strategy Results Overall Performance on VSI-Bench Impact of Training Data Size & ...

Its encoder-decoder architecture ensures strong performance in both raw and fine-tuned states, making it a balanced choice for users seeking a middle ground between quality and model size.

The model utilizes a pre-trained frozen CLIP vision encoder ViT-L/14 for visual feature generation. To convert these visual features into a fixed number of tokens, the model employs a module known as ...

Recent research sheds light on the strengths and weaknesses of encoder-decoder and decoder-only models architectures in machine translation tasks.

Key Takeaways: Llama 3.2 integrates a pre-trained image encoder with a language model using cross-attention layers to handle both vision and text tasks. The 11B and 90B models excel in tasks like ...