33 citations · 72 across the 12 of their papers we have counts for
13 papers
Attention-based Class Activation Diffusion for Weakly-Supervised Semantic Segmentation
Jianqiang Huang, Jian Wang, Qianru Sun +1
Extracting class activation maps (CAM) is a key step for weakly-supervised semantic segmentation (WSSS). The CAM of convolution neural networks fails to capture long-range feature…
Respecting Transfer Gap in Knowledge Distillation
Yulei Niu, Long Chen, Chang Zhou +1
Knowledge distillation (KD) is essentially a process of transferring a teacher model's behavior, e.g., network response, to a student model. The network response serves as addition…
Class Re-Activation Maps for Weakly-Supervised Semantic Segmentation
Zhaozheng Chen, Tan Wang, Xiongwei Wu +3
Extracting class activation maps (CAM) is arguably the most standard step of generating pseudo masks for weakly-supervised semantic segmentation (WSSS). Yet, we find that the crux…
Introspective Distillation for Robust Question Answering
Yulei Niu, Hanwang Zhang
Question answering (QA) models are well-known to exploit data bias, e.g., the language prior in visual QA and the position bias in reading comprehension. Recent debiasing methods a…
Self-Supervised Learning Disentangled Group Representation as Feature
Tan Wang, Zhongqi Yue, Jianqiang Huang +2
A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics). In…
Are Missing Links Predictable? An Inferential Benchmark for Knowledge Graph Completion
Yixin Cao, Xiang Ji, Xin Lv +3
We present InferWiki, a Knowledge Graph Completion (KGC) dataset that improves upon existing benchmarks in inferential ability, assumptions, and patterns. First, each testing sampl…