… To overcome these challenges, we propose Deformable … the sparse DCN operator for
practical efficiency. DCNv4 comes with a much faster implementation and an improved operator …

Environment: We use an A100 80GB SXM GPU to benchmark throughput on all experiments.
The software environment is PyTorch 1.13, CUDA 11.7, cuDNN 8.5. When testing Flash …

… visual tokens, prohibiting the applications on high-resolution … to various local modeling
operators, including different types … deformed locations of sparse keys could achieve an efficient …

… , so that our model not only has the large effective receptive … the core operator of InternImage
is a dynamic sparse convolution … Revisiting DCNv2. A straightforward way to bridge the gap …

… Efficient deformable convnets: Rethinking dynamic and … Efficient deformable convnets:
Rethinking dynamic and sparse operator for vision applications. arXiv preprint arXiv:2401.06197, …

… Similar to the Vision Transformer (ViT), our model is designed to efficiently handle … Efficient
deformable convnets: Rethinking dynamic and sparse operator for vision applications. arXiv …

… images in computer vision applications are apparent … two critical purposes: (1) efficiently
adapting the frozen CLIP model to … To provide a detailed rethinking process of the deformable …

… By introducing the self-attention mechanism and redefining the … This study improved the
deformable convolution part of the … DCNv4 is an efficient dynamic sparse operator that uses …

… recently, some works start to rethink the limitations of the split… computer vision which are
ubiquitous in real-world applications. … for processing voxels efficiently is sparse convolution[201, …

… In this comparison, we adopt the deformable convolution v3 (… due to its sparse and binary
nature, which limits information … AI and data-centric AI, particularly exploring their applications …