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Found 5 papers, 1 papers with code
Consistency Matters: Explore LLMs Consistency From a Black-Box Perspective
The solution to this problem is often time-consuming and labor-intensive, and there is also an additional cost of secondary deployment, resulting in economic and time losses.
SeqCo-DETR: Sequence Consistency Training for Self-Supervised Object Detection with Transformers
To this end, we propose SeqCo-DETR, a novel Sequence Consistency-based self-supervised method for object DEtection with TRansformers.
Geo6D: Geometric Constraints Learning for 6D Pose Estimation
Numerous 6D pose estimation methods have been proposed that employ end-to-end regression to directly estimate the target pose parameters.
Uni6Dv2: Noise Elimination for 6D Pose Estimation
Uni6D is the first 6D pose estimation approach to employ a unified backbone network to extract features from both RGB and depth images.
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
A common practice is to select the highly confident predictions as the pseudo ground-truth, but it leads to a problem that most pixels may be left unused due to their unreliability.
