HQ-SAM is only trained on the introduced detaset of 44k masks, which takes only 4 hours on 8 GPUs.
In this paper, we present CodeTF, an open-source Transformer-based library for state-of-the-art Code LLMs and code intelligence.
Augmented Language Models (ALMs) blend the reasoning capabilities of Large Language Models (LLMs) with tools that allow for knowledge retrieval and action execution.
We present XPhoneBERT, the first multilingual model pre-trained to learn phoneme representations for the downstream text-to-speech (TTS) task.
Ranked #1 on Speech Synthesis on North American English
To analyze video, we use 3D reconstructions from HMR 2. 0 as input to a tracking system that operates in 3D.
Ranked #3 on Pose Tracking on PoseTrack2018
Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance.
Ranked #1 on Action Recognition on AVA v2.2 (using extra training data)
Human driver can easily describe the complex traffic scene by visual system.
Large language models (LLMs) have shown excellent performance on various tasks, but the astronomical model size raises the hardware barrier for serving (memory size) and slows down token generation (memory bandwidth).
Large Language Models (LLMs) have seen an impressive wave of advances recently, with models now excelling in a variety of tasks, such as mathematical reasoning and program synthesis.
Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference.