Concerns with enabling computers to interpret and understand visual inputs, such as images and videos.
This article presents Mamba-ND, a design that extends the Mamba architecture to multi-dimensional data. Transformers, the de-facto architecture for sequence modeling, have significant compute and memory complexity. Mamba, a state…
Continue readingThe Segment Anything Model (SAM) is a popular image processing tool for its segmentation accuracy, variety of input prompts, training capabilities, and efficient model design. However, its application to ultrasound…
Continue readingThe article introduces a novel method called Point-VOS for Video Object Segmentation (VOS). Traditional VOS methods require dense per-object mask annotations which are time-consuming and costly. Point-VOS, however, utilizes a…
Continue readingThe paper presents a novel method for generating PBR images directly, avoiding the challenges and inaccuracies associated with RGB generation and extraction. Existing methods for fine-tuning the weights of a…
Continue readingThe article introduces SPHINX-X, a Multi-modality Large Language Model (MLLM) series, which is an enhancement of the SPHINX framework. The researchers have improved the architecture and training efficiency by removing…
Continue readingThe study presents InstaGen, a novel method to enhance object detector’s ability by training on synthetic dataset generated from diffusion models. The authors integrated an instance-level grounding head into a…
Continue readingThe paper discusses AttnLRP, a method that extends Layer-wise Relevance Propagation to handle attention layers in transformer models. It aims to provide better understanding of the reasoning process of these…
Continue readingThe article introduces WEBLINX, a large-scale benchmark for conversational web navigation. It covers a broad range of patterns on over 150 real-world websites. The authors designed a model that prunes…
Continue readingThe paper proposes CREMA, a new efficient and modular modality-fusion framework for video reasoning. This model enhances the flexibility and efficiency of multimodal compositional reasoning approaches by allowing for the…
Continue readingThe newly released Segment Anything Model (SAM) is a popular tool used in image processing due to its superior segmentation accuracy, input prompts, training capabilities, and efficient model design. However,…
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