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Sökning: WFRF:(Gu Jian) > Konferensbidrag

  • Resultat 1-4 av 4
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1.
  • Bhat, Goutam, et al. (författare)
  • NTIRE 2022 Burst Super-Resolution Challenge
  • 2022
  • Ingår i: 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2022). - : IEEE. - 9781665487399 - 9781665487405 ; , s. 1040-1060
  • Konferensbidrag (refereegranskat)abstract
    • Burst super-resolution has received increased attention in recent years due to its applications in mobile photography. By merging information from multiple shifted images of a scene, burst super-resolution aims to recover details which otherwise cannot be obtained using a simple input image. This paper reviews the NTIRE 2022 challenge on burst super-resolution. In the challenge, the participants were tasked with generating a clean RGB image with 4x higher resolution, given a RAW noisy burst as input. That is, the methods need to perform joint denoising, demosaicking, and super-resolution. The challenge consisted of 2 tracks. Track 1 employed synthetic data, where pixel-accurate high-resolution ground truths are available. Track 2 on the other hand used real-world bursts captured from a handheld camera, along with approximately aligned reference images captured using a DSLR. 14 teams participated in the final testing phase. The top performing methods establish a new state-of-the-art on the burst super-resolution task.
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2.
  • Cabrera Arteaga, Javier, 1992-, et al. (författare)
  • Superoptimization of WebAssembly bytecode
  • 2020
  • Ingår i: Conference Companion of the 4th International Conference on Art, Science, and Engineering of Programming. - Portugal : Aakar Books.
  • Konferensbidrag (refereegranskat)abstract
    • Motivated by the fast adoption of WebAssembly, we propose the first functional pipeline to support the superoptimization of WebAssembly bytecode. Our pipeline works over LLVM and Souper. We evaluate our superoptimization pipeline with 12 programs from the Rosetta code project. Our pipeline improves the code section size of 8 out of 12 programs. We discuss the challenges faced in superoptimization of WebAssembly with two case studies.
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3.
  • Gu, Jian, et al. (författare)
  • Multimodal Representation for Neural Code Search
  • 2021
  • Ingår i: 2021 IEEE international conference on software maintenance and evolution (ICSME 2021). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 483-494
  • Konferensbidrag (refereegranskat)abstract
    • Semantic code search is about finding semantically relevant code snippets for a given natural language query. In the state-of-the-art approaches, the semantic similarity between code and query is quantified as the distance of their representation in the shared vector space. In this paper, to improve the vector space, we introduce tree-serialization methods on a simplified form of AST and build the multimodal representation for the code data. We conduct extensive experiments using a single corpus that is large-scale and multi-language: CodeSearchNet. Our results show that both our tree-serialized representations and multimodal learning model improve the performance of code search. Last, we define intuitive quantification metrics oriented to the completeness of semantic and syntactic information of the code data, to help understand the experimental findings.
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  • Resultat 1-4 av 4

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