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09/19/2023
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Autonomous Driving
Annotating 3D LiDAR point clouds for perception tasks including 3D objec...
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09/07/2023
ImageBind-LLM: Multi-modality Instruction Tuning
We present ImageBind-LLM, a multi-modality instruction tuning method of ...
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08/26/2023
Beyond One-to-One: Rethinking the Referring Image Segmentation
Referring image segmentation aims to segment the target object referred ...
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08/25/2023
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Large language models (LLMs) have revolutionized natural language proces...
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08/11/2023
Foundation Model is Efficient Multimodal Multitask Model Selector
This paper investigates an under-explored but important problem: given a...
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08/07/2023
Tiny LVLM-eHub: Early Multimodal Experiments with Bard
Recent advancements in Large Vision-Language Models (LVLMs) have demonst...
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07/07/2023
GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest
Instruction tuning large language model (LLM) on image-text pairs has ac...
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06/20/2023
Align, Adapt and Inject: Sound-guided Unified Image Generation
Text-guided image generation has witnessed unprecedented progress due to...
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06/15/2023
LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models
Large Vision-Language Models (LVLMs) have recently played a dominant rol...
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05/29/2023
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers
Token compression aims to speed up large-scale vision transformers (e.g....
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03/29/2023
Real-time Controllable Denoising for Image and Video
Controllable image denoising aims to generate clean samples with human p...
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07/07/2022
Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space
This paper addresses an important problem of ranking the pre-trained dee...
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06/08/2022
CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving
Unsupervised contrastive learning for indoor-scene point clouds has achi...
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12/05/2021
Dynamic Token Normalization Improves Vision Transformer
Vision Transformer (ViT) and its variants (e.g., Swin, PVT) have achieve...
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05/13/2021
BWCP: Probabilistic Learning-to-Prune Channels for ConvNets via Batch Whitening
This work presents a probabilistic channel pruning method to accelerate ...
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02/29/2020
Channel Equilibrium Networks for Learning Deep Representation
Convolutional Neural Networks (CNNs) are typically constructed by stacki...
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08/16/2019
Differentiable Learning-to-Group Channels via Groupable Convolutional Neural Networks
Group convolution, which divides the channels of ConvNets into groups, h...
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08/16/2019
Differentiable Learning-to-Group Channels viaGroupable Convolutional Neural Networks
Group convolution, which divides the channels of ConvNets into groups, h...
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03/09/2019
SSN: Learning Sparse Switchable Normalization via SparsestMax
Normalization methods improve both optimization and generalization of Co...
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01/02/2019
Learning Efficient Detector with Semi-supervised Adaptive Distillation
Knowledge Distillation (KD) has been used in image classification for mo...
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09/04/2018