VisualData Learning Loss for Active Learning

Learning Loss for Active Learning

[Service Development Team, Kyunghwan Lee] We usually encounter unlabeled data bundles in the process of learning a model, and often run into data annotation problems. Labeling all unlabeled data is too time-consuming and expensive...

VisualTrendCode Learning Loss for Active Learning

Unity ML-Agents v2.0

[Service Development Team Jeon Jeon-Jun] ML-Agents, unveiled by Unity, is an open source tool that creates virtual characters in the game environment. You can create a game environment and learn NPC characters (Agents) that can operate in the environment through algorithms such as reinforcement learning.…

Visual Learning Loss for Active Learning

MoveNet: A JavaScript pose estimator

[Prior Research Team Yoo Hee-jo] Pose estimation is one of the visual processing technologies that tracks the movement of characters in a video. Body landmarks, which are similar to facial landmarks, are extracted and connected to describe the posture of the entire body. Most of…

VisualTrend Learning Loss for Active Learning

MetaHuman Creator-Unreal Engine

[Service Development Team Byungin Kim] MetaHuman Creator is a digital human creation tool recently released by Epic Games. It looks similar to the character creation of an MMORPG game, but it is very difficult to implement such a real-time digital human, and it is a very time-consuming task. It is easy to rig, hair,...

VisualTrend Learning Loss for Active Learning

ImageNet and privacy

ImageNet is a dataset that has greatly influenced the advancement of AI technology so that no one knows about AI researchers. Consisting of a large number of images and their metadata, this dataset consists of approximately 14 million images...