Motion Forecasting on Argoverse CVPR 2020

Metric: minADE (K=1) (higher is better)

LeaderboardDataset

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Results

#	Model↕	minADE (K=1)▼	Extra Data	Paper	Date↕	Code
1	ewta	10634487.5868	No	-	-	-
2	jwlhs104	38.9455	No	-	-	-
3	Johnny Hsieh	32.9034	No	-	-	-
4	WST	30.7524	No	-	-	-
5	cxl	22.3728	No	-	-	-
6	BaseballBro	17.0122	No	-	-	-
7	tusiji12138	14.9928	No	-	-	-
8	Constant velocity map prior	12.3146	No	-	-	-
9	Lane_vae	11.3861	No	-	-	-
10	mtz	7.4994	No	-	-	-
11	DQS	7.1746	No	-	-	-
12	D0.2	5.8841	No	-	-	-
13	xjtub09	5.7132	No	-	-	-
14	wangwentong	5.5699	No	-	-	-
15	CoderTeam	4.9745	No	-	-	-
16	AttnLstmMultiMod_fix	4.7665	No	-	-	-
17	Whatever	4.7286	No	-	-	-
18	suu	4.6564	No	-	-	-
19	rishabh	4.4824	No	-	-	-
20	GRU_CVAE	4.4349	No	-	-	-
21	Online_CL	3.9771	No	-	-	-
22	BD	3.9521	No	-	-	-
23	ffffx	3.9358	No	-	-	-
24	SHM	3.7408	No	-	-	-
25	Gilgamesh	3.6495	No	-	-	-
26	NCTU-BNN	3.6495	No	-	-	-
27	yellowtaxi	3.5646	No	-	-	-
28	zlewe	3.5333	No	-	-	-
29	NCTU_309512033	3.5333	No	-	-	-
30	null	3.5333	No	-	-	-
31	baseline_argo_contant_vel_01	3.5333	No	-	-	-
32	test_1	3.5333	No	-	-	-
33	mmmddd	3.5333	No	-	-	-
34	HYU_ACE	3.467	No	-	-	-
35	NCTU-heheEECS	3.4549	No	-	-	-
36	NN(map)	3.4549	No	-	-	-
37	NN	3.4549	No	-	-	-
38	hell	3.4549	No	-	-	-
39	Ruochen	3.4152	No	-	-	-
40	Speculators	3.3858	No	-	-	-
41	RuSheng	3.3726	No	-	-	-
42	randommm	3.3098	No	-	-	-
43	Tim	3.3035	No	-	-	-
44	Trial	3.2553	No	-	-	-
45	vectornet	3.1088	No	-	-	-
46	xjh199923	3.0551	No	-	-	-
47	hale	3.0338	No	-	-	-
48	Model Agnostic Meta Learning	3.0107	No	-	-	-
49	rush	3.0009	No	-	-	-
50	zs	2.9871	No	-	-	-
51	Aaron Huang	2.9838	No	-	-	-
52	HH	2.9719	No	-	-	-
53	Funtastic_4casting	2.9631	No	-	-	-
54	Constant-V-Forecating(very very naive)	2.9631	No	-	-	-
55	DeepPrediction	2.9631	No	-	-	-
56	lllsssjQuery33108037804872914465_1678097593292	2.9631	No	-	-	-
57	MT-PNC	2.9631	No	-	-	-
58	naive method test	2.9631	No	-	-	-
59	default	2.9631	No	-	-	-
60	efficent and adaptive	2.9631	No	-	-	-
61	Anonymous1234	2.9576	No	-	-	-
62	gogogo_zhigang	2.9498	No	-	-	-
63	Alice_Bob	2.9337	No	-	-	-
64	Holmes	2.9076	No	-	-	-
65	llh	2.9029	No	-	-	-
66	posterior with best parameters	2.8257	No	-	-	-
67	TangBug	2.8104	No	-	-	-
68	6 mode model	2.797	No	-	-	-
69	Vi yulia 51 prob	2.7949	No	-	-	-
70	huhu	2.771	No	-	-	-
71	parallel_tl_123_0224	2.7484	No	-	-	-
72	haomo	2.7385	No	-	-	-
73	pph	2.7291	No	-	-	-
74	zys	2.7271	No	-	-	-
75	xmy	2.7262	No	-	-	-
76	lixin	2.6885	No	-	-	-
77	lstm+cnn	2.6883	No	-	-	-
78	bartosz	2.6784	No	-	-	-
79	Map Static+Specific	2.6392	No	-	-	-
80	Waldo	2.6003	No	-	-	-
81	0626	2.5911	No	-	-	-
82	multimodal	2.5904	No	-	-	-
83	fs_test	2.5888	No	-	-	-
84	deleted_accout_because_of_submission_error	2.5448	No	-	-	-
85	baguette	2.5344	No	-	-	-
86	gg6666	2.5329	No	-	-	-
87	DGA_lg	2.4627	No	-	-	-
88	adl	2.4611	No	-	-	-
89	slf	2.4611	No	-	-	-
90	team_moe	2.4228	No	-	-	-
91	que_anr	2.418	No	-	-	-
92	BNet-2S	2.4032	No	-	-	-
93	lanegcn_pimp_curr_sgd	2.3896	No	-	-	-
94	Multiple Trajectories	2.3865	No	-	-	-
95	haomokeji	2.3805	No	-	-	-
96	Anchor	2.3379	No	-	-	-
97	mt_navi	2.3148	No	-	-	-
98	fs	2.3053	No	-	-	-
99	grip	2.2923	No	-	-	-
100	arky	2.2842	No	-	-	-
101	LSTMs	2.2831	No	-	-	-
102	Tang Luqi	2.2719	No	-	-	-
103	DF-RNN	2.2709	No	-	-	-
104	msms	2.2558	No	-	-	-
105	Fong	2.232	No	-	-	-
106	NCTU-GPL-GPAL	2.2283	No	-	-	-
107	par	2.2181	No	-	-	-
108	miaomiao	2.1962	No	-	-	-
109	JMT	2.1902	No	-	-	-
110	GoodMountain	2.1875	No	-	-	-
111	Habitat-Web	2.174	No	-	-	-
112	TNT - CoRL20	2.174	No	TNT: Target-driveN Trajectory Prediction	2020-08-19	Code
113	El Camino	2.1728	No	-	-	-
114	Challenge	2.1686	No	-	-	-
115	TestForecast	2.1461	No	-	-	-
116	Xiaogang	2.1416	No	-	-	-
117	timtim	2.1057	No	-	-	-
118	huangmozhi	2.0987	No	-	-	-
119	Parallel x-transformers version1.1	2.0558	No	-	-	-
120	raster-to-svg-train(t70.5k-train120k)1e-4-2-bs5-39k	2.0489	No	-	-	-
121	TNT_20220819	2.0414	No	-	-	-
122	huangmozhi9527	2.0401	No	-	-	-
123	CMAN(av1_demo)	2.0363	No	-	-	-
124	cls-token-transfer208k	2.0031	No	-	-	-
125	TrajectoryOracle	2.0029	No	-	-	-
126	SCP	1.9953	No	-	-	-
127	zhanzhenxueyuan	1.986	No	-	-	-
128	Alibaba-ADLab	1.9673	No	-	-	-
129	lagat_mm	1.9536	No	-	-	-
130	Extended-Social-LSTM	1.9424	No	-	-	-
131	Social-CVAE	1.9276	No	-	-	-
132	Array	1.9152	No	-	-	-
133	raster_v2	1.9123	No	-	-	-
134	lstm	1.9108	No	-	-	-
135	PRIME	1.9105	No	-	-	-
136	ln	1.9103	No	-	-	-
137	uulm-mrm	1.9044	No	-	-	-
138	SCP	1.9016	No	-	-	-
139	player	1.8988	No	-	-	-
140	somemethod	1.89	No	-	-	-
141	leige	1.8785	No	-	-	-
142	tnt-mtp_100s_targetloss_1-1_6	1.8768	No	-	-	-
143	HGO (K=6)	1.8763	No	-	-	-
144	tjxu	1.8705	No	-	-	-
145	tmtkinu	1.8684	No	-	-	-
146	idlaber-Hans	1.8637	No	-	-	-
147	UAR	1.8599	No	-	-	-
148	argo_test_18_5m_add_rotation_change_data_change_model_3_01	1.8594	No	-	-	-
149	vector-net-latest	1.8525	No	-	-	-
150	FGNet	1.8521	No	-	-	-
151	chant	1.8436	No	-	-	-
152	tp	1.8426	No	-	-	-
153	AutoBot-Ego	1.8397	No	-	-	-
154	HTTP	1.8386	No	-	-	-
155	xjh	1.8335	No	-	-	-
156	MultiLine	1.8312	No	-	-	-
157	phuang	1.8312	No	-	-	-
158	wimp	1.8233	No	-	-	-
159	dis102500	1.8179	No	-	-	-
160	CRAT-Pred	1.8162	No	CRAT-Pred: Vehicle Trajectory Prediction with Cr...	2022-02-09	Code
161	SceneTransformer	1.8108	No	-	-	-
162	wo_longterm	1.8103	No	-	-	-
163	1mode-groupEmbed-160000	1.809	No	-	-	-
164	1mode-groupEmbed-106000	1.8062	No	-	-	-
165	MTN	1.803	No	-	-	-
166	Tang Luqi	1.8014	No	-	-	-
167	pred	1.7995	No	-	-	-
168	ORIGINAL	1.7988	No	-	-	-
169	JAL-MTP	1.7978	No	-	-	-
170	ulimit	1.7902	No	-	-	-
171	MR	1.7874	No	-	-	-
172	Tang Luqi	1.7812	No	-	-	-
173	ISY@TK	1.7762	No	-	-	-
174	mmTransformer	1.7737	No	-	-	-
175	mmppgg	1.7732	No	-	-	-
176	fyyclass	1.7721	No	-	-	-
177	FTGN	1.7716	No	Trajectory Forecasting on Temporal Graphs	2022-07-01	Code
178	numberEight	1.7491	No	-	-	-
179	l_DGA_lg	1.7453	No	-	-	-
180	leon	1.7438	No	-	-	-
181	Jean	1.7414	No	-	-	-
182	Model0	1.7396	No	-	-	-
183	Lotus	1.7368	No	-	-	-
184	sihong	1.7365	No	-	-	-
185	Waypoint	1.735	No	-	-	-
186	cxx	1.7343	No	-	-	-
187	Shangguan_IFS	1.7338	No	-	-	-
188	LaneGCN-s	1.731	No	-	-	-
189	gcu_v2	1.7303	No	-	-	-
190	sample_replace_gt_smalln_82	1.73	No	-	-	-
191	huyuening	1.7288	No	-	-	-
192	PRANK	1.7284	No	PRANK: motion Prediction based on RANKing	2020-10-22	-
193	PRANK	1.7284	No	PRANK: motion Prediction based on RANKing	2020-10-22	-
194	LaneGCN-trainset-36	1.7252	No	-	-	-
195	SCM+Distill(best model)	1.7239	No	-	-	-
196	s1	1.7191	No	-	-	-
197	Transformer1	1.7189	No	-	-	-
198	fyyyy	1.7176	No	-	-	-
199	lanegcn_12_epoch	1.7168	No	-	-	-
200	lengyue	1.7163	No	-	-	-
201	Jack-M	1.715	No	-	-	-
202	William	1.712	No	-	-	-
203	FRM	1.7063	No	Leveraging Future Relationship Reasoning for Veh...	2023-05-24	-
204	vill	1.7061	No	-	-	-
205	LGN	1.706	No	-	-	-
206	Europa	1.7055	No	-	-	-
207	15 train 40e	1.7041	No	-	-	-
208	Miss Rate	1.7029	No	-	-	-
209	YuNi	1.7024	No	-	-	-
210	watson	1.7024	No	-	-	-
211	CY_ng	1.7024	No	-	-	-
212	cbc	1.7024	No	-	-	-
213	julie-1	1.7024	No	-	-	-
214	ywyeh	1.7024	No	-	-	-
215	hitchhiker	1.7024	No	-	-	-
216	alfred	1.7024	No	-	-	-
217	hitljx_test_sub	1.7024	No	-	-	-
218	chailiang	1.7024	No	-	-	-
219	zhousihong	1.7024	No	-	-	-
220	LaneGCN	1.7019	No	-	-	-
221	yiqi-fudan	1.7012	No	-	-	-
222	scale4	1.7001	No	-	-	-
223	abac	1.6997	No	-	-	-
224	HOME + GOHOME	1.6986	No	HOME: Heatmap Output for future Motion Estimation	2021-05-23	Code
225	vilab	1.698	No	-	-	-
226	SenseTime_AP	1.6973	No	-	-	-
227	mymodel7_actornet_2_mapnet_a2m_a2a_222	1.6968	No	-	-	-
228	(VI)	1.6906	No	-	-	-
229	GOHOME	1.6887	No	GOHOME: Graph-Oriented Heatmap Output for future...	2021-09-04	-
230	vi_avp	1.6883	No	-	-	-
231	prediction-liangdian	1.6864	No	-	-	-
232	MFT	1.6856	No	-	-	-
233	LaneRCNN (IROS 2021)	1.6852	No	LaneRCNN: Distributed Representations for Graph-...	2021-01-17	-
234	daiyongjie	1.6837	No	-	-	-
235	minFDE	1.6791	No	-	-	-
236	DSP	1.6788	No	-	-	-
237	88	1.6768	No	-	-	-
238	TPA+Laneloss	1.6737	No	-	-	-
239	damplyv1	1.6737	No	-	-	-
240	ToNet	1.6724	No	-	-	-
241	mm_kk_parallel_distemb_91	1.6702	No	-	-	-
242	THOMAS	1.6686	No	THOMAS: Trajectory Heatmap Output with learned M...	2021-10-13	-
243	just_a_test	1.6666	No	-	-	-
244	Hi_base	1.6602	No	-	-	-
245	cls-weight1-5	1.6588	No	-	-	-
246	brier36	1.6585	No	-	-	-
247	ATDSNet-v2	1.6572	No	-	-	-
248	MacFormer	1.6565	No	TENET: Transformer Encoding Network for Effectiv...	2022-06-30	-
249	FGNet_sub	1.6561	No	-	-	-
250	cul2	1.6557	No	-	-	-
251	MSPre	1.6547	No	-	-	-
252	DIDI	1.6492	No	-	-	-
253	xia	1.6453	No	-	-	-
254	lstm_v1	1.645	No	-	-	-
255	ECARX-V1	1.6427	No	-	-	-
256	cls_weight1.2-decoder5-use-last	1.6405	No	-	-	-
257	decoder-3-last	1.6377	No	-	-	-
258	Wayformer	1.636	No	Wayformer: Motion Forecasting via Simple & Effic...	2022-07-12	Code
259	SSL-Lanes	1.6342	No	SSL-Lanes: Self-Supervised Learning for Motion F...	2022-06-28	Code
260	DTNet(FDE)	1.6338	No	-	-	-
261	ATTTHOM	1.632	No	-	-	-
262	HIKVISION-ADLab-hz	1.6287	No	-	-	-
263	matrix_mugen	1.6266	No	-	-	-
264	vectorgcn	1.6262	No	-	-	-
265	be_s2lossf_3846	1.6244	No	-	-	-
266	whr_test	1.6242	No	-	-	-
267	multipath++	1.6235	No	MultiPath++: Efficient Information Fusion and Tr...	2021-11-29	Code
268	Dcupqiu	1.6225	No	-	-	-
269	CU-aware LaneGCN	1.6217	No	-	-	-
270	LTP	1.6214	No	-	-	-
271	m2a2_34	1.6186	No	-	-	-
272	TO	1.6124	No	-	-	-
273	chl(yiqi)	1.6117	No	-	-	-
274	Met	1.6072	No	-	-	-
275	HiVT-128	1.5984	No	-	-	Code
276	ussm v2-SAIPS	1.5969	No	-	-	-
277	Ameame	1.5959	No	-	-	-
278	GANet	1.5921	No	GANet: Goal Area Network for Motion Forecasting	2022-09-20	Code
279	EuclidNet-L	1.5852	No	-	-	-
280	lt_tv_cont	1.5851	No	-	-	-
281	R-Pred	1.5843	No	R-Pred: Two-Stage Motion Prediction Via Tube-Que...	2022-11-16	-
282	TPCN	1.5752	No	TPCN: Temporal Point Cloud Networks for Motion F...	2021-03-04	-
283	ProIn_av1	1.5737	No	-	-	-
284	Holistic Transformer	1.5692	No	Holistic Transformer: A Joint Neural Network for...	2022-06-17	-
285	Gnet	1.5689	No	-	-	-
286	HiVT++	1.5619	No	-	-	Code
287	PAGA	1.5599	No	-	-	-
288	LAformer	1.5531	No	-	-	-
289	lt_cont_k6	1.5407	No	-	-	-
290	DuanZX	1.5349	No	-	-	-
291	FFINet	1.5327	No	-	-	-
292	QCNet	1.5234	No	-	-	Code
293	VI LaneIter	1.5181	No	-	-	-
294	TSGN	1.5111	No	-	-	-
295	TPCN++	1.5099	No	-	-	-
296	shernan_wu	1.5097	No	-	-	-
297	ProphNet	1.491	No	-	-	-
298	DCMS	1.4768	No	Bootstrap Motion Forecasting With Self-Consisten...	2022-04-12	-
299	SEPT	1.4412	No	-	-	-

Model↕

minADE (K=1)▼

Extra Data

Paper

Date↕

Code

ewta

10634487.5868

jwlhs104

38.9455

Johnny Hsieh

32.9034

WST

30.7524

cxl

22.3728

BaseballBro

17.0122

tusiji12138

14.9928

Constant velocity map prior

12.3146

Lane_vae

11.3861

mtz

7.4994

DQS

7.1746

D0.2

5.8841

xjtub09

5.7132

wangwentong

5.5699

CoderTeam

4.9745

AttnLstmMultiMod_fix

4.7665

Whatever

4.7286

suu

4.6564

rishabh

4.4824

GRU_CVAE

4.4349

Online_CL

3.9771

3.9521

ffffx

3.9358

SHM

3.7408

Gilgamesh

3.6495

NCTU-BNN

3.6495

yellowtaxi

3.5646

zlewe

3.5333

NCTU_309512033

3.5333

null

3.5333

baseline_argo_contant_vel_01

3.5333

test_1

3.5333

mmmddd

3.5333

HYU_ACE

3.467

NCTU-heheEECS

3.4549

NN(map)

3.4549

hell

3.4549

Ruochen

3.4152

Speculators

3.3858

RuSheng

3.3726

randommm

3.3098

Tim

3.3035

Trial

3.2553

vectornet

3.1088

xjh199923

3.0551

hale

3.0338

Model Agnostic Meta Learning

3.0107

rush

3.0009

2.9871

Aaron Huang

2.9838

2.9719

Funtastic_4casting

2.9631

Constant-V-Forecating(very very naive)

2.9631

DeepPrediction

2.9631

lllsssjQuery33108037804872914465_1678097593292

2.9631

MT-PNC

2.9631

naive method test

2.9631

default

2.9631

efficent and adaptive

2.9631

Anonymous1234

2.9576

gogogo_zhigang

2.9498

Alice_Bob

2.9337

Holmes

2.9076

llh

2.9029

posterior with best parameters

2.8257

TangBug

2.8104

6 mode model

2.797

Vi yulia 51 prob

2.7949

huhu

2.771

parallel_tl_123_0224

2.7484

haomo

2.7385

pph

2.7291

zys

2.7271

xmy

2.7262

lixin

2.6885

lstm+cnn

2.6883

bartosz

2.6784

Map Static+Specific

2.6392

Waldo

2.6003

0626

2.5911

multimodal

2.5904

fs_test

2.5888

deleted_accout_because_of_submission_error

2.5448

baguette

2.5344

gg6666

2.5329

DGA_lg

2.4627

adl

2.4611

slf

2.4611

team_moe

2.4228

que_anr

2.418

BNet-2S

2.4032

lanegcn_pimp_curr_sgd

2.3896

Multiple Trajectories

2.3865

haomokeji

2.3805

Anchor

2.3379

mt_navi

2.3148

2.3053

grip

2.2923

100

arky

2.2842

101

LSTMs

2.2831

102

Tang Luqi

2.2719

103

DF-RNN

2.2709

104

msms

2.2558

105

Fong

2.232

106

NCTU-GPL-GPAL

2.2283

107

par

2.2181

108

miaomiao

2.1962

109

JMT

2.1902

110

GoodMountain

2.1875

111

Habitat-Web

2.174

112

TNT - CoRL20

2.174

TNT: Target-driveN Trajectory Prediction

2020-08-19

Code

113

El Camino

2.1728

114

Challenge

2.1686

115

TestForecast

2.1461

116

Xiaogang

2.1416

117

timtim

2.1057

118

huangmozhi

2.0987

119

Parallel x-transformers version1.1

2.0558

120

raster-to-svg-train(t70.5k-train120k)1e-4-2-bs5-39k

2.0489

121

TNT_20220819

2.0414

122

huangmozhi9527

2.0401

123

CMAN(av1_demo)

2.0363

124

cls-token-transfer208k

2.0031

125

TrajectoryOracle

2.0029

126

SCP

1.9953

127

zhanzhenxueyuan

1.986

128

Alibaba-ADLab

1.9673

129

lagat_mm

1.9536

130

Extended-Social-LSTM

1.9424

131

Social-CVAE

1.9276

132

Array

1.9152

133

raster_v2

1.9123

134

lstm

1.9108

135

PRIME

1.9105

136

1.9103

137

uulm-mrm

1.9044

138

SCP

1.9016

139

player

1.8988

140

somemethod

1.89

141

leige

1.8785

142

tnt-mtp_100s_targetloss_1-1_6

1.8768

143

HGO (K=6)

1.8763

144

tjxu

1.8705

145

tmtkinu

1.8684

146

idlaber-Hans

1.8637

147

UAR

1.8599

148

argo_test_18_5m_add_rotation_change_data_change_model_3_01

1.8594

149

vector-net-latest

1.8525

150

FGNet

1.8521

151

chant

1.8436

152

1.8426

153

AutoBot-Ego

1.8397

154

HTTP

1.8386

155

xjh

1.8335

156

MultiLine

1.8312

157

phuang

1.8312

158

wimp

1.8233

159

dis102500

1.8179

160

CRAT-Pred

1.8162

CRAT-Pred: Vehicle Trajectory Prediction with Cr...

2022-02-09

Code

161

SceneTransformer

1.8108

162

wo_longterm

1.8103

163

1mode-groupEmbed-160000

1.809

164

1mode-groupEmbed-106000

1.8062

165

MTN

1.803

166

Tang Luqi

1.8014

167

pred

1.7995

168

ORIGINAL

1.7988

169

JAL-MTP

1.7978

170

ulimit

1.7902

171

1.7874

172

Tang Luqi

1.7812

173

ISY@TK

1.7762

174

mmTransformer

1.7737

175

mmppgg

1.7732

176

fyyclass

1.7721

177

FTGN

1.7716

Trajectory Forecasting on Temporal Graphs

2022-07-01

Code

178

numberEight

1.7491

179

l_DGA_lg

1.7453

180

leon

1.7438

181

Jean

1.7414

182

Model0

1.7396

183

Lotus

1.7368

184

sihong

1.7365

185

Waypoint

1.735

186

cxx

1.7343

187

Shangguan_IFS

1.7338

188

LaneGCN-s

1.731

189

gcu_v2

1.7303

190

sample_replace_gt_smalln_82

1.73

191

huyuening

1.7288

192

PRANK

1.7284

PRANK: motion Prediction based on RANKing

2020-10-22

193

PRANK

1.7284

PRANK: motion Prediction based on RANKing

2020-10-22

194

LaneGCN-trainset-36

1.7252

195

SCM+Distill(best model)

1.7239

196

1.7191

197

Transformer1

1.7189

198

fyyyy

1.7176

199

lanegcn_12_epoch

1.7168

200

lengyue

1.7163

201

Jack-M

1.715

202

William

1.712

203

FRM

1.7063

Leveraging Future Relationship Reasoning for Veh...

2023-05-24

204

vill

1.7061

205

LGN

1.706

206

Europa

1.7055

207

15 train 40e

1.7041

208

Miss Rate

1.7029

209

YuNi

1.7024

210

watson

1.7024

211

CY_ng

1.7024

212

cbc

1.7024

213

julie-1

1.7024

214

ywyeh

1.7024

215

hitchhiker

1.7024

216

alfred

1.7024

217

hitljx_test_sub

1.7024

218

chailiang

1.7024

219

zhousihong

1.7024

220

LaneGCN

1.7019

221

yiqi-fudan

1.7012

222

scale4

1.7001

223

abac

1.6997

224

HOME + GOHOME

1.6986

HOME: Heatmap Output for future Motion Estimation

2021-05-23

Code

225

vilab

1.698

226

SenseTime_AP

1.6973

227

mymodel7_actornet_2_mapnet_a2m_a2a_222

1.6968

228

(VI)

1.6906

229

GOHOME

1.6887

GOHOME: Graph-Oriented Heatmap Output for future...

2021-09-04

230

vi_avp

1.6883

231

prediction-liangdian

1.6864

232

MFT

1.6856

233

LaneRCNN (IROS 2021)

1.6852

LaneRCNN: Distributed Representations for Graph-...

2021-01-17

234

daiyongjie

1.6837

235

minFDE

1.6791

236

DSP

1.6788

237

1.6768

238

TPA+Laneloss

1.6737

239

damplyv1

1.6737

240

ToNet

1.6724

241

mm_kk_parallel_distemb_91

1.6702

242

THOMAS

1.6686

THOMAS: Trajectory Heatmap Output with learned M...

2021-10-13

243

just_a_test

1.6666

244

Hi_base

1.6602

245

cls-weight1-5

1.6588

246

brier36

1.6585

247

ATDSNet-v2

1.6572

248

MacFormer

1.6565

TENET: Transformer Encoding Network for Effectiv...

2022-06-30

249

FGNet_sub

1.6561

250

cul2

1.6557

251

MSPre

1.6547

252

DIDI

1.6492

253

xia

1.6453

254

lstm_v1

1.645

255

ECARX-V1

1.6427

256

cls_weight1.2-decoder5-use-last

1.6405

257

decoder-3-last

1.6377

258

Wayformer

1.636

Wayformer: Motion Forecasting via Simple & Effic...

2022-07-12

Code

259

SSL-Lanes

1.6342

SSL-Lanes: Self-Supervised Learning for Motion F...

2022-06-28

Code

260

DTNet(FDE)

1.6338

261

ATTTHOM

1.632

262

HIKVISION-ADLab-hz

1.6287

263

matrix_mugen

1.6266

264

vectorgcn

1.6262

265

be_s2lossf_3846

1.6244

266

whr_test

1.6242

267

multipath++

1.6235

MultiPath++: Efficient Information Fusion and Tr...

2021-11-29

Code

268

Dcupqiu

1.6225

269

CU-aware LaneGCN

1.6217

270

LTP

1.6214

271

m2a2_34

1.6186

272

1.6124

273

chl(yiqi)

1.6117

274

Met

1.6072

275

HiVT-128

1.5984

Code

276

ussm v2-SAIPS

1.5969

277

Ameame

1.5959

278

GANet

1.5921

GANet: Goal Area Network for Motion Forecasting

2022-09-20

Code

279

EuclidNet-L

1.5852

280

lt_tv_cont

1.5851

281

R-Pred

1.5843

R-Pred: Two-Stage Motion Prediction Via Tube-Que...

2022-11-16

282

TPCN

1.5752

TPCN: Temporal Point Cloud Networks for Motion F...

2021-03-04

283

ProIn_av1

1.5737

284

Holistic Transformer

1.5692

Holistic Transformer: A Joint Neural Network for...

2022-06-17

285

Gnet

1.5689

286

HiVT++

1.5619

Code

287

PAGA

1.5599

288

LAformer

1.5531

289

lt_cont_k6

1.5407

290

DuanZX

1.5349

291

FFINet

1.5327

292

QCNet

1.5234

Code

293

VI LaneIter

1.5181

294

TSGN

1.5111

295

TPCN++

1.5099

296

shernan_wu

1.5097

297

ProphNet

1.491

298

DCMS

1.4768

Bootstrap Motion Forecasting With Self-Consisten...

2022-04-12

299

SEPT

1.4412