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06/26/2023
FunQA: Towards Surprising Video Comprehension
Surprising videos, e.g., funny clips, creative performances, or visual i...
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06/08/2023
MIMIC-IT: Multi-Modal In-Context Instruction Tuning
High-quality instructions and responses are essential for the zero-shot ...
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05/30/2023
Learning without Forgetting for Vision-Language Models
Class-Incremental Learning (CIL) or continual learning is a desired capa...
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05/16/2023
Latent Distribution Adjusting for Face Anti-Spoofing
With the development of deep learning, the field of face anti-spoofing (...
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05/05/2023
Otter: A Multi-Modal Model with In-Context Instruction Tuning
Large language models (LLMs) have demonstrated significant universal cap...
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01/31/2023
What Makes Good Examples for Visual In-Context Learning?
Large-scale models trained on broad data have recently become the mainst...
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12/17/2022
3D Point Cloud Pre-training with Knowledge Distillation from 2D Images
The recent success of pre-trained 2D vision models is mostly attributabl...
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09/15/2022
On-Device Domain Generalization
We present a systematic study of domain generalization (DG) for tiny neu...
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07/14/2022
Benchmarking Omni-Vision Representation through the Lens of Visual Realms
Though impressive performance has been achieved in specific visual realm...
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06/09/2022
Neural Prompt Search
The size of vision models has grown exponentially over the last few year...
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04/27/2022
Robust Face Anti-Spoofing with Dual Probabilistic Modeling
The field of face anti-spoofing (FAS) has witnessed great progress with ...
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03/15/2022
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy
Large-scale datasets play a vital role in computer vision. Existing data...
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02/25/2021
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
As facial interaction systems are prevalently deployed, security and rel...
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07/24/2020
