101 citations · 277 across the 18 of their papers we have counts for
13 papers · 1 filter
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +4
Recently, large-scale pre-trained language-image models like CLIP have shown extraordinary capabilities for understanding spatial contents, but naively transferring such models to…
RLIPv2: Fast Scaling of Relational Language-Image Pre-training
Hangjie Yuan, Shiwei Zhang, Xiang Wang +7
Relational Language-Image Pre-training (RLIP) aims to align vision representations with relational texts, thereby advancing the capability of relational reasoning in computer visio…
ModelScope Text-to-Video Technical Report
Jiuniu Wang, Hangjie Yuan, Dayou Chen +3
This paper introduces ModelScopeT2V, a text-to-video synthesis model that evolves from a text-to-image synthesis model (i.e., Stable Diffusion). ModelScopeT2V incorporates spatio-t…
Temporally-Adaptive Models for Efficient Video Understanding
Ziyuan Huang, Shiwei Zhang, Liang Pan +4
Spatial convolutions are extensively used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in diffe…
CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic Segmentation
Jun Cen, Shiwei Zhang, Yixuan Pei +5
2D RGB images and 3D LIDAR point clouds provide complementary knowledge for the perception system of autonomous vehicles. Several 2D and 3D fusion methods have been explored for th…
VideoComposer: Compositional Video Synthesis with Motion Controllability
Xiang Wang, Hangjie Yuan, Shiwei Zhang +6
The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis. However, achieving controllable vide…
MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Zhiwu Qing +4
Current state-of-the-art approaches for few-shot action recognition achieve promising performance by conducting frame-level matching on learned visual features. However, they gener…
Enlarging Instance-specific and Class-specific Information for Open-set Action Recognition
Jun Cen, Shiwei Zhang, Xiang Wang +4
Open-set action recognition is to reject unknown human action cases which are out of the distribution of the training set. Existing methods mainly focus on learning better uncertai…
CLIP-guided Prototype Modulating for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Jun Cen +4
Learning from large-scale contrastive language-image pre-training like CLIP has shown remarkable success in a wide range of downstream tasks recently, but it is still under-explore…
VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation
Zhengxiong Luo, Dayou Chen, Yingya Zhang +6
A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate ne…
The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition
Jun Cen, Di Luan, Shiwei Zhang +5
Open-set Recognition (OSR) aims to identify test samples whose classes are not seen during the training process. Recently, Unified Open-set Recognition (UOSR) has been proposed to…
Distribution Adaptive INT8 Quantization for Training CNNs
Kang Zhao, Sida Huang, Pan Pan +4
Researches have demonstrated that low bit-width (e.g., INT8) quantization can be employed to accelerate the inference process. It makes the gradient quantization very promising sin…
Visual Search at Alibaba
Yanhao Zhang, Pan Pan, Yun Zheng +4
This paper introduces the large scale visual search algorithm and system infrastructure at Alibaba. The following challenges are discussed under the E-commercial circumstance at Al…