Titlebook: Computer Vision – ECCV 2018; 15th European Confer Vittorio Ferrari,Martial Hebert,Yair Weiss Conference proceedings 2018 Springer Nature Sw

Ganglion

COWER

Semi-convolutional Operators for Instance Segmentationhese problems to pixel labeling tasks, as the latter could be more efficient, could be integrated seamlessly in image-to-image network architectures as used in many other tasks, and could be more accurate for objects that are not well approximated by bounding boxes. In this paper we show theoretical

改革運(yùn)動(dòng)

滔滔不絕地講

Fictitious GAN: Training GANs with Historical Modelse. GANs are commonly viewed as a two-player zero-sum game between two neural networks. Here, we leverage this game theoretic view to study the convergence behavior of the training process. Inspired by the fictitious play learning process, a novel training method, referred to as Fictitious GAN, is in

洞穴

火光在搖曳

C-WSL: Count-Guided Weakly Supervised Localization weakly supervised localization (WSL). C-WSL uses a simple count-based region selection algorithm to select high-quality regions, each of which covers a single object instance during training, and improves existing WSL methods by training with the selected regions. To demonstrate the effectiveness o

輕打

先驅(qū)

Product Quantization Network for Fast Image Retrievale hard assignment to soft assignment, we make it feasible to incorporate the product quantization as a layer of a convolutional neural network and propose our product quantization network. Meanwhile, we come up with a novel asymmetric triplet loss, which effectively boosts the retrieval accuracy of

BAIT

Cross-Modal Hamming Hashingt provide with the advantages of computation efficiency and retrieval quality for multimedia retrieval. Hamming space retrieval enables efficient constant-time search that returns data items within a given Hamming radius to each query, by hash lookups instead of linear scan. However, Hamming space r

HAIL