In order to thrive in hostile and ever-changing natural environments, mammalian brains evolved to store large amounts of knowledge about the world and continually integrate new information while avoiding catastrophic forgetting.
In addition, we identify two anime-specific challenges of distorted and faint hand-drawn lines and unwanted color artifacts.
By harnessing the potent generative capabilities of pre-trained large video diffusion models, we propose NVS-Solver, a new novel view synthesis (NVS) paradigm that operates \textit{without} the need for training.
Compared to both open-source and proprietary models, InternVL 1. 5 shows competitive performance, achieving state-of-the-art results in 8 of 18 benchmarks.
Ranked #6 on Visual Question Answering on MM-Vet
Yuan 2. 0-M32, with a similar base architecture as Yuan-2. 0 2B, uses a mixture-of-experts architecture with 32 experts of which 2 experts are active.
We present the first enrollment interface where the wearer looks at the target speaker for a few seconds to capture a single, short, highly noisy, binaural example of the target speaker.
End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities.
To address this, we propose a diffusion-based 4D occupancy generation model, OccSora, to simulate the development of the 3D world for autonomous driving.
This raises the question: can we achieve flexibility in the number of visual tokens to suit different tasks and computational resources?
We address this challenge by introducing state-space models (SSMs) with learnable timescale parameters to event-based vision.
Ranked #3 on Object Detection on GEN1 Detection