3 citations · 10 across the 12 of their papers we have counts for
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ByteNet: Rethinking Multimedia File Fragment Classification through Visual Perspectives
Wenyang Liu, Kejun Wu, Tianyi Liu +3
Multimedia file fragment classification (MFFC) aims to identify file fragment types, e.g., image/video, audio, and text without system metadata. It is of vital importance in multim…
Symmetric Multi-Similarity Loss for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2024
Xiaoqi Wang, Yi Wang, Lap-Pui Chau
In this report, we present our champion solution for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge in CVPR 2024. Essentially, this challenge differs from traditional visual-…
Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method
Tianyi Liu, Kejun Wu, Yi Wang +3
The past decade has witnessed great strides in video recovery by specialist technologies, like video inpainting, completion, and error concealment. However, they typically simulate…
ExposureDiffusion: Learning to Expose for Low-light Image Enhancement
Yufei Wang, Yi Yu, Wenhan Yang +4
Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed…
A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings
Wenyang Liu, Yi Wang, Kejun Wu +2
File fragment classification (FFC) on small chunks of memory is essential in memory forensics and Internet security. Existing methods mainly treat file fragments as 1d byte signals…
Raw Image Reconstruction with Learned Compact Metadata
Yufei Wang, Yi Yu, Wenhan Yang +4
While raw images exhibit advantages over sRGB images (e.g., linearity and fine-grained quantization level), they are not widely used by common users due to the large storage requir…