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Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection. (arXiv:2308.05426v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Foundation models, such as OpenAI's GPT-3 and GPT-4, Meta's LLaMA, and
Google's PaLM2, have revolutionized the field of artificial intelligence. A
notable paradigm shift has been the advent of the Segment Anything Model (SAM),
which has exhibited a remarkable capability to segment real-world objects,
trained on 1 billion masks and 11 million images. Although SAM excels in
general object segmentation, it lacks the intrinsic ability to detect salient
objects, resulting in suboptimal performance in this domain. To address this
challenge, …
artificial artificial intelligence arxiv capability detection foundation google gpt gpt-3 gpt-4 intelligence llama low meta objects openai palm2 paradigm sam segment anything model shift world