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Found 7 papers, 0 papers with code
DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation
DriveDreamer-2 is the first world model to generate customized driving videos, it can generate uncommon driving videos (e. g., vehicles abruptly cut in) in a user-friendly manner.
WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens
World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation.
DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving
The established world model holds immense potential for the generation of high-quality driving videos, and driving policies for safe maneuvering.
WebFace260M: A Benchmark for Million-Scale Deep Face Recognition
For a comprehensive evaluation of face matchers, three recognition tasks are performed under standard, masked and unbiased settings, respectively.
Masked Face Recognition Challenge: The WebFace260M Track Report
There are second phase of the challenge till October 1, 2021 and on-going leaderboard.
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training data, as well as an elaborately designed time-constrained evaluation protocol.
Ranked #1 on
Face Verification
on IJB-C
(training dataset metric)
Attention-guided Unified Network for Panoptic Segmentation
This paper studies panoptic segmentation, a recently proposed task which segments foreground (FG) objects at the instance level as well as background (BG) contents at the semantic level.
Ranked #24 on
Panoptic Segmentation
on COCO test-dev
