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09/14/2023
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning
Recently, large-scale pre-trained language-image models like CLIP have s...
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08/18/2023
RLIPv2: Fast Scaling of Relational Language-Image Pre-training
Relational Language-Image Pre-training (RLIP) aims to align vision repre...
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07/27/2023
Regularized Mask Tuning: Uncovering Hidden Knowledge in Pre-trained Vision-Language Models
Prompt tuning and adapter tuning have shown great potential in transferr...
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06/03/2023
VideoComposer: Compositional Video Synthesis with Motion Controllability
The pursuit of controllability as a higher standard of visual content cr...
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04/03/2023
MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition
Current state-of-the-art approaches for few-shot action recognition achi...
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03/15/2023
Scanning Only Once: An End-to-end Framework for Fast Temporal Grounding in Long Videos
Video temporal grounding aims to pinpoint a video segment that matches t...
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03/13/2023
ViM: Vision Middleware for Unified Downstream Transferring
Foundation models are pre-trained on massive data and transferred to dow...
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03/09/2023
Cones: Concept Neurons in Diffusion Models for Customized Generation
Human brains respond to semantic features of presented stimuli with diff...
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03/06/2023
CLIP-guided Prototype Modulating for Few-shot Action Recognition
Learning from large-scale contrastive language-image pre-training like C...
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03/01/2023
Rethinking Efficient Tuning Methods from a Unified Perspective
Parameter-efficient transfer learning (PETL) based on large-scale pre-tr...
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02/20/2023
Composer: Creative and Controllable Image Synthesis with Composable Conditions
Recent large-scale generative models learned on big data are capable of ...
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02/14/2023
UKnow: A Unified Knowledge Protocol for Common-Sense Reasoning and Vision-Language Pre-training
This work presents a unified knowledge protocol, called UKnow, which fac...
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11/29/2022
Dimensionality-Varying Diffusion Process
Diffusion models, which learn to reverse a signal destruction process to...
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11/21/2022
Neural Dependencies Emerging from Learning Massive Categories
This work presents two astonishing findings on neural networks learned f...
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09/20/2022
Improving GANs with A Dynamic Discriminator
Discriminator plays a vital role in training generative adversarial netw...
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06/13/2022
Rank Diminishing in Deep Neural Networks
The rank of neural networks measures information flowing across layers. ...
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05/21/2022
Principled Knowledge Extrapolation with GANs
Human can extrapolate well, generalize daily knowledge into unseen scena...
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06/10/2020
On Noise Injection in Generative Adversarial Networks
Noise injection has been proved to be one of the key technique advances ...
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03/31/2020
In-Domain GAN Inversion for Real Image Editing
Recent work has shown that a variety of controllable semantics emerges i...
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03/08/2020
Perceptual Image Super-Resolution with Progressive Adversarial Network
Single Image Super-Resolution (SISR) aims to improve resolution of small...
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12/21/2019
Latent Variables on Spheres for Sampling and Spherical Inference
Variational inference is a fundamental problem in Variational Auto-Encod...
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06/27/2019
Curriculum Learning for Deep Generative Models with Clustering
Training generative models like generative adversarial networks (GANs) a...
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06/19/2019
LIA: Latently Invertible Autoencoder with Adversarial Learning
Deep generative models play an increasingly important role in machine le...
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07/27/2018
Few Shot Learning with Simplex
Deep learning has made remarkable achievement in many fields. However, l...
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11/17/2014
Errata: Distant Supervision for Relation Extraction with Matrix Completion
The essence of distantly supervised relation extraction is that it is an...
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07/05/2014
Homophilic Clustering by Locally Asymmetric Geometry
Clustering is indispensable for data analysis in many scientific discipl...
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08/25/2012
