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Found 8 papers, 6 papers with code
ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation
The proposed ScribFormer model has a triple-branch structure, i. e., the hybrid of a CNN branch, a Transformer branch, and an attention-guided class activation map (ACAM) branch.
Ranked #1 on
Semantic Segmentation
on ACDC Scribbles
Reconstructing Hands in 3D with Transformers
The key to HaMeR's success lies in scaling up both the data used for training and the capacity of the deep network for hand reconstruction.
ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding
We evaluate ScribbleVC on three benchmark datasets and compare it with state-of-the-art methods.
Ranked #2 on
Semantic Segmentation
on ACDC Scribbles
Coarse-to-Fine Covid-19 Segmentation via Vision-Language Alignment
Segmentation of COVID-19 lesions can assist physicians in better diagnosis and treatment of COVID-19.
Ranked #1 on
Medical Image Segmentation
on MosMedData
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
VISOR annotates videos from EPIC-KITCHENS, which comes with a new set of challenges not encountered in current video segmentation datasets.
When Did It Happen? Duration-informed Temporal Localization of Narrated Actions in Vlogs
We consider the task of temporal human action localization in lifestyle vlogs.
COHESIV: Contrastive Object and Hand Embedding Segmentation In Video
In this paper we learn to segment hands and hand-held objects from motion.
Understanding Human Hands in Contact at Internet Scale
Hands are the central means by which humans manipulate their world and being able to reliably extract hand state information from Internet videos of humans engaged in their hands has the potential to pave the way to systems that can learn from petabytes of video data.
