Referring expression comprehension(REC)aims to locate a specific region in an image described by a natural language.Existing two-stage methods generate multiple candidate proposals in the first stage,followed by selec...Referring expression comprehension(REC)aims to locate a specific region in an image described by a natural language.Existing two-stage methods generate multiple candidate proposals in the first stage,followed by selecting one of these proposals as the grounding result in the second stage.Nevertheless,the number of candidate proposals generated in the first stage significantly exceeds ground truth and the recall of critical objects is inadequate,thereby enormously limiting the overall network performance.To address the above issues,the authors propose an innovative method termed Separate Non-Maximum Suppression(Sep-NMS)for two-stage REC.Particularly,Sep-NMS models information from the two stages independently and collaboratively,ultimately achieving an overall improvement in comprehension and identification of the target objects.Specifically,the authors propose a Ref-Relatedness module for filtering referent proposals rigorously,decreasing the redundancy of referent proposals.A CLIP†Relatedness module based on robust multimodal pre-trained encoders is built to precisely assess the relevance between language and proposals to improve the recall of critical objects.It is worth mentioning that the authors are the pioneers in utilising a multimodal pre-training model for proposal filtering in the first stage.Moreover,an Information Fusion module is designed to effectively amalgamate the multimodal information across two stages,ensuring maximum uti-lisation of the available information.Extensive experiments demonstrate that the approach achieves competitive performance with previous state-of-the-art methods.The datasets used are publicly available:RefCOCO,RefCOCO+:https://doi.org/10.1007/978-3-319-46475-6_5 and RefCOCOg:https://doi.org/10.1109/CVPR.2016.9.展开更多
The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically ...The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically characterized the transcript changes in the adherens junction pathway following injury. In this study, a rat model of sciatic nerve crush injury was established by forceps. Deep sequencing data were analyzed using comprehensive transcriptome analysis at 0, 1, 4, 7, and 14 days after injury. Results showed that most individual molecules in the adherens junctions were either upregulated or downregulated after nerve injury. The m RNA expression of ARPC1 B, ARPC3, TUBA8, TUBA1 C, CTNNA2, ACTN3, MET, HGF, NME1 and ARF6, which are involved in the adherens junction pathway and in remodeling of adherens junctions, was analyzed using quantitative real-time polymerase chain reaction. Most of these genes were upregulated in the sciatic nerve stump following peripheral nerve injury, except for CTNNA2, which was downregulated. Our findings reveal the dynamic changes of key molecules in adherens junctions and in remodeling of adherens junctions. These key genes provide a reference for the selection of clinical therapeutic targets for peripheral nerve injury.展开更多
基金funded by the National Natural Science Foundation of China(No.62076032).
文摘Referring expression comprehension(REC)aims to locate a specific region in an image described by a natural language.Existing two-stage methods generate multiple candidate proposals in the first stage,followed by selecting one of these proposals as the grounding result in the second stage.Nevertheless,the number of candidate proposals generated in the first stage significantly exceeds ground truth and the recall of critical objects is inadequate,thereby enormously limiting the overall network performance.To address the above issues,the authors propose an innovative method termed Separate Non-Maximum Suppression(Sep-NMS)for two-stage REC.Particularly,Sep-NMS models information from the two stages independently and collaboratively,ultimately achieving an overall improvement in comprehension and identification of the target objects.Specifically,the authors propose a Ref-Relatedness module for filtering referent proposals rigorously,decreasing the redundancy of referent proposals.A CLIP†Relatedness module based on robust multimodal pre-trained encoders is built to precisely assess the relevance between language and proposals to improve the recall of critical objects.It is worth mentioning that the authors are the pioneers in utilising a multimodal pre-training model for proposal filtering in the first stage.Moreover,an Information Fusion module is designed to effectively amalgamate the multimodal information across two stages,ensuring maximum uti-lisation of the available information.Extensive experiments demonstrate that the approach achieves competitive performance with previous state-of-the-art methods.The datasets used are publicly available:RefCOCO,RefCOCO+:https://doi.org/10.1007/978-3-319-46475-6_5 and RefCOCOg:https://doi.org/10.1109/CVPR.2016.9.
基金supported by the National Natural Science Foundation of China,No.31700926the Priority Academic Program Development of Jiangsu Higher Education Institutions of China
文摘The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically characterized the transcript changes in the adherens junction pathway following injury. In this study, a rat model of sciatic nerve crush injury was established by forceps. Deep sequencing data were analyzed using comprehensive transcriptome analysis at 0, 1, 4, 7, and 14 days after injury. Results showed that most individual molecules in the adherens junctions were either upregulated or downregulated after nerve injury. The m RNA expression of ARPC1 B, ARPC3, TUBA8, TUBA1 C, CTNNA2, ACTN3, MET, HGF, NME1 and ARF6, which are involved in the adherens junction pathway and in remodeling of adherens junctions, was analyzed using quantitative real-time polymerase chain reaction. Most of these genes were upregulated in the sciatic nerve stump following peripheral nerve injury, except for CTNNA2, which was downregulated. Our findings reveal the dynamic changes of key molecules in adherens junctions and in remodeling of adherens junctions. These key genes provide a reference for the selection of clinical therapeutic targets for peripheral nerve injury.
